WorldWideScience

Sample records for profiles stability predictions

  1. Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

    Science.gov (United States)

    Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

    2017-10-01

    Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (pdisorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Gene expression profiling of breast tumor cell lines to predict for therapeutic response to microtubule-stabilizing agents.

    Science.gov (United States)

    Kadra, Gais; Finetti, Pascal; Toiron, Yves; Viens, Patrice; Birnbaum, Daniel; Borg, Jean-Paul; Bertucci, François; Gonçalves, Anthony

    2012-04-01

    Microtubule-targeting agents, including taxanes (Tax) and ixabepilone (Ixa), are important components of modern breast cancer chemotherapy regimens, but no molecular parameter is currently available that can predict for their efficiency. We sought to develop pharmacogenomic predictors of Tax- and Ixa-response from a large panel of human breast tumor cell lines (BTCL), then to evaluate their performance in clinical samples. Thirty-two BTCL, representative of the molecular diversity of breast cancers (BC), were treated in vitro with Tax (paclitaxel (Pac), docetaxel (Doc)), and ixabepilone (Ixa), then classified as drug-sensitive or resistant according to their 50% inhibitory concentrations (IC50s). Baseline gene expression data were obtained using Affymetrix U133 Plus 2.0 human oligonucleotide microarrays. Gene expression set (GES) predictors of response to taxanes were derived, then tested for validation internally and in publicly available gene expression datasets. In vitro IC50s of Pac and Doc were almost identical, whereas some Tax-resistant BTCL retained sensitivity to Ixa. GES predictors for Tax-sensitivity (333 genes) and Ixa-sensitivity (79 genes) were defined. They displayed a limited number of overlapping genes. Both were validated by leave-n-out cross-validation (n = 4; for overall accuracy (OA), P = 0.028 for Tax, and P = 0.0005 for Ixa). The GES predictor of Tax-sensitivity was tested on publicly available external datasets and significantly predicted Pac-sensitivity in 16 BTCL (P = 0.04 for OA), and pathological complete response to Pac-based neoadjuvant chemotherapy in BC patients (P = 0.0045 for OA). Applying Tax and Ixa-GES to a dataset of clinically annotated early BC patients identified subsets of tumors with potentially distinct phenotypes of drug sensitivity: predicted Ixa-sensitive/Tax-resistant BC were significantly (P Tax-sensitive BC. Genomic predictors for Tax- and Ixa-sensitivity can be derived from BTCL and may be helpful for better

  3. Geographic Profiling: Knowledge Through Prediction

    Science.gov (United States)

    2014-06-01

    acts. In general, geographic profiling “is based on crime pattern, routine activity, and rational choice theories from environmental criminology , a...Information Systems and Crime Analysis , ed. Fahui Wang (Hershey, PA: Idea Group, 2005), 104. 3 models to the actual outcomes and determine the...order to construct a geographic profile, the coordinates of crime scenes are entered into a software analysis program that contains an algorithm known

  4. Prediction of turning stability using receptance coupling

    Science.gov (United States)

    Jasiewicz, Marcin; Powałka, Bartosz

    2018-01-01

    This paper presents an issue of machining stability prediction of dynamic "lathe - workpiece" system evaluated using receptance coupling method. Dynamic properties of the lathe components (the spindle and the tailstock) are assumed to be constant and can be determined experimentally based on the results of the impact test. Hence, the variable of the system "machine tool - holder - workpiece" is the machined part, which can be easily modelled analytically. The method of receptance coupling enables a synthesis of experimental (spindle, tailstock) and analytical (machined part) models, so impact testing of the entire system becomes unnecessary. The paper presents methodology of analytical and experimental models synthesis, evaluation of the stability lobes and experimental validation procedure involving both the determination of the dynamic properties of the system and cutting tests. In the summary the experimental verification results would be presented and discussed.

  5. Genetic and environmental influences on personality profile stability : Unraveling the normativeness problem

    NARCIS (Netherlands)

    Bleidorn, W.; Kandler, C.; Riemann, R.; Angleitner, A.; Spinath, F.M.

    2012-01-01

    The present study is the first to disentangle the genetic and environmental influences on personality profile stability. Spanning a period of 10 years, we analyzed the etiology of 3 aspects of profile stability (overall profile stability, distinctive profile stability, and profile normativeness)

  6. Profile stabilization of tilt mode in a Field Reversed Configuration

    Energy Technology Data Exchange (ETDEWEB)

    Cobb, J.W.; Tajima, T. [Texas Univ., Austin, TX (United States). Inst. for Fusion Studies; Barnes, D.C. [Los Alamos National Lab., NM (United States)

    1993-06-01

    The possibility of stabilizing the tilt mode in Field Reversed Configurations without resorting to explicit kinetic effects such as large ion orbits is investigated. Various pressure profiles, P({Psi}), are chosen, including ``hollow`` profiles where current is strongly peaked near the separatrix. Numerical equilibria are used as input for an initial value simulation which uses an extended Magnetohydrodynamic (MHD) model that includes viscous and Hall terms. Tilt stability is found for specific hollow profiles when accompanied by high values of separatrix beta, {beta}{sub sep}. The stable profiles also have moderate to large elongation, racetrack separatrix shape, and lower values of 3, average ratio of Larmor radius to device radius. The stability is unaffected by changes in viscosity, but the neglect of the Hall term does cause stable results to become marginal or unstable. Implications for interpretation of recent experiments are discussed.

  7. Towards predicting the stability of protein-stabilized emulsions

    NARCIS (Netherlands)

    Delahaije, R.J.B.M.; Gruppen, H.; Giuseppin, M.L.F.; Wierenga, P.A.

    2015-01-01

    The protein concentration is known to determine the stability against coalescence during formation of emulsions. Recently, it was observed that the protein concentration also influences the stability of formed emulsions against flocculation as a result of changes in the ionic strength. In both

  8. WEB-THERMODYN: sequence analysis software for profiling DNA helical stability

    OpenAIRE

    Huang, Yanlin; Kowalski, David

    2003-01-01

    WEB-THERMODYN analyzes DNA sequences and computes the DNA helical stability, i.e. the free energy required to unwind and separate the strands of the double helix. A helical stability profile across a selected DNA region or the entire sequence is generated by sliding-window analysis. WEB-THERMODYN can predict sites of low helical stability present at regulatory regions for transcription and replication and can be used to test the influence of mutations. The program can be accessed at: http://w...

  9. Stability of cocaine impurity profiles during 12 months of storage

    DEFF Research Database (Denmark)

    Nielsen, Louise Stride; Villesen, Palle; Lindholst, Christian

    2016-01-01

    During the lifetime of a cocaine batch from production end to consumption, several alterations may occur, leading to possible changes in the original impurity profile. Such profile changes may eventually result in erroneous forensic evaluations. In the present study, the stability of both...... the alkaloid and the residual solvent impurity profiles of cocaine were evaluated over a period of 12 months under different storage conditions (temperature, purity and weight) using GC-MS and HS-GC-MS, respectively. The sample purity (p ... profile. The most significant change was observed in low purity samples stored at 37 °C. In contrast, no changes were observed in the residual solvent profile at all storage conditions for the entire 12-month study period. This finding indicates...

  10. Predicting Marital Happiness and Stability from Newlywed Interactions.

    Science.gov (United States)

    Gottman, John M.; Coan, James; Carrere, Sybil; Swanson, Catherine

    1998-01-01

    Marital interaction processes that are predictive of divorce or marital stability and processes that discriminate between happily and unhappily married stable couples are explored (N=130). Seven types of process models are examined, and results are discussed. Divorce and stability were predicted with 83% accuracy, and satisfaction with 80%…

  11. Adaptive method for electron bunch profile prediction

    Directory of Open Access Journals (Sweden)

    Alexander Scheinker

    2015-10-01

    Full Text Available We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.

  12. Predicting vegetation-stabilized dune morphology

    Science.gov (United States)

    Barchyn, T.; Hugenholtz, C.

    2012-04-01

    The morphology of vegetation-stabilized dune fields on the North American Great Plains mostly comprises parabolic dunes; stabilized barchan and transverse dunes are rare. One notable exception is the Nebraska Sand Hills (NSH), where massive grass-covered barchan and transverse dunes bear proof of former desert-like conditions. We present a hypothesis from a numerical dune field model to explain the vegetation-stabilized morphology of dunes. The model incorporates a growth curve that preferentially grows vegetation in regions of sediment deposition with a sharp drop in growth at the peak depositional tolerance of vegetation, qualitatively matching biological response to erosion and deposition. Simulations on a range of pre-stabilization dune morphologies, from large closely-spaced transverse dunes to small dispersed barchans, indicate that the stabilized morphology is largely determined by the ratio of slipface deposition rate to peak depositional tolerance of vegetation. Conceptually, slipface deposition rate is related to dune height and celerity. By keeping depositional tolerance constant (representing a constant vegetation type and climate) the model shows that large slow-moving dunes have low slipface deposition rates and essentially 'freeze' in place once vegetation is introduced, retaining their pre-vegetation morphology. Small fast-moving dunes have higher slipface deposition rates and evolve into parabolic dunes. We hypothesize that, when barchan and transverse dunes are subjected to a stabilizing climate shift that increases vegetation growth rate, they retain their pre-stabilization morphology if deposition rates are below the depositional tolerance of stabilizing vegetation, otherwise they become parabolic dunes. This could explain why NSH dunes are stabilized in barchan and transverse morphologies while elsewhere on the Great Plains dune fields are dominated by smaller parabolic dunes.

  13. SteadyCom: Predicting microbial abundances while ensuring community stability.

    Directory of Open Access Journals (Sweden)

    Siu Hung Joshua Chan

    2017-05-01

    Full Text Available Genome-scale metabolic modeling has become widespread for analyzing microbial metabolism. Extending this established paradigm to more complex microbial communities is emerging as a promising way to unravel the interactions and biochemical repertoire of these omnipresent systems. While several modeling techniques have been developed for microbial communities, little emphasis has been placed on the need to impose a time-averaged constant growth rate across all members for a community to ensure co-existence and stability. In the absence of this constraint, the faster growing organism will ultimately displace all other microbes in the community. This is particularly important for predicting steady-state microbiota composition as it imposes significant restrictions on the allowable community membership, composition and phenotypes. In this study, we introduce the SteadyCom optimization framework for predicting metabolic flux distributions consistent with the steady-state requirement. SteadyCom can be rapidly converged by iteratively solving linear programming (LP problem and the number of iterations is independent of the number of organisms. A significant advantage of SteadyCom is compatibility with flux variability analysis. SteadyCom is first demonstrated for a community of four E. coli double auxotrophic mutants and is then applied to a gut microbiota model consisting of nine species, with representatives from the phyla Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. In contrast to the direct use of FBA, SteadyCom is able to predict the change in species abundance in response to changes in diets with minimal additional imposed constraints on the model. By randomizing the uptake rates of microbes, an abundance profile with a good agreement to experimental gut microbiota is inferred. SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment.

  14. Fast Prediction of DNA Melting Bubbles Using DNA Thermodynamic Stability.

    Science.gov (United States)

    Zrimec, Jan; Lapanje, Ales

    2015-01-01

    DNA melting bubbles are the basis of many DNA-protein interactions, such as those in regulatory DNA regions driving gene expression, DNA replication and bacterial horizontal gene transfer. Bubble formation is affected by DNA duplex stability and thermally induced duplex destabilization (TIDD). Although prediction of duplex stability with the nearest neighbor (NN) method is much faster than prediction of TIDD with the Peyrard-Bishop-Dauxois (PBD) model, PBD predicted TIDD defines regulatory DNA regions with higher accuracy and detail. Here, we considered that PBD predicted TIDD is inherently related to the intrinsic duplex stabilities of destabilization regions. We show by regression modeling that NN duplex stabilities can be used to predict TIDD almost as accurately as is predicted with PBD. Predicted TIDD is in fact ascribed to non-linear transformation of NN duplex stabilities in destabilization regions as well as effects of neighboring regions relative to destabilization size. Since the prediction time of our models is over six orders of magnitude shorter than that of PBD, the models present an accessible tool for researchers. TIDD can be predicted on our webserver at http://tidd.immt.eu.

  15. Slurry discharge management-beach profile prediction

    Energy Technology Data Exchange (ETDEWEB)

    Bravo, R.; Nawrot, J.R. [Southern Illinois University at Carbondale, Carbondale, IL (United States). Dept. of Civil Engineering

    1996-11-01

    Mine tailings dams are embankments used by the mining industry to retain the tailings products after the mineral preparation process. Based on the acid-waste stereotype that all coal slurry is acid producing, current reclamation requires a four foot soil cover for inactive slurry disposal areas. Compliance with this requirement is both difficult and costly and in some case unnecessary, as not all the slurry, or portions of slurry impoundments are acid producing. Reduced costs and recent popularity of wetland development has prompted many operators to request reclamation variances for slurry impoundments. Waiting to address slurry reclamation until after the impoundment is full, limits the flexibility of reclamation opportunities. This paper outlines a general methodology to predict the formation of the beach profile for mine tailings dams, by the discharge volume and location of the slurry into the impoundment. The review is presented under the perspective of geotechnical engineering and waste disposal management emphasizing the importance of pre-planning slurry disposal land reclamation. 4 refs., 5 figs.

  16. Development of stabilized tenofovir disoproxil tablet: degradation profile, stabilization, and bioequivalence in beagle dogs.

    Science.gov (United States)

    Oh, Ga-Hui; Kim, Joo-Eun; Park, Young-Joon

    2017-12-25

    The purpose of this study was to develop a hydrolysis-resistant optimized oral formulation of tenofovir disoproxil (TD) using a stabilizer. To develop a stabilized TD tablet bioequivalent to the commercial TD fumarate (TDF, Viread ® ) tablet, TD free base was prepared and its degradation profile and stability were investigated. The TD tablet showed antiviral activity, but its absorption was limited in the intestinal tract because of premature degradation. The drug subjected to severe conditions for the stress test was catalyzed under neutral, basic, oxidative, and thermolytic conditions, whereas it was comparatively stable under acidic, photolytic, and humid states. The compatibility study showed that sodium bisulfite (SB) stabilized TD by preventing its degradation in aqueous and 3% peroxide solutions compared with the unstabilized TD. According to the stability analysis and degradation profile, four TD tablet formulations were prepared. The selected TD tablets were composed of non-hygroscopic excipients (lipophilic-fumed silica, anhydrous lactose, and microcrystalline cellulose [MCC]), SB, croscarmellose sodium (CCS), and hydrogenated castor oil (HCO), and were manufactured using a dry granulation method because of their hydrolytic properties. The stabilized TD tablet showed similar dissolution properties as the TDF (Viread ® ) reference tablet in pH 1.2, 4.0, and 6.8 and water. Moreover, the lower degradation rate of the tablet in simulated gastrointestinal fluid demonstrated that its intestinal absorption might have improved owing to prevention of its enzymatic hydrolysis and the pH effect. Finally, the formulated TD tablet was bioequivalent to the TDF (Viread ® ) reference tablet in beagle dogs.

  17. Confinement and stability of plasmas with externally driven steady-state elevated q-profiles

    Energy Technology Data Exchange (ETDEWEB)

    Bock, Alexander; Stober, Joerg; Fischer, Rainer; Fable, Emiliano; Reich, Matthias [Max-Planck-Institut fuer Plasmaphysik, Garching bei Muenchen (Germany); Collaboration: ASDEX Upgrade Team

    2015-05-01

    The helicity profile of the magnetic field lines is an important quantity for the operation of Tokamak fusion devices and can be expressed as the so-called safety factor q. It has profound influence on both the stability of the fusion plasma, as well as its confinement properties. Operation scenarios with centrally elevated and flat, or even reversed q-profiles promise fewer central instabilities and better core confinement and are thus considered potentially attractive for future fusion power plants. To verify these predictions, centrally elevated q-profiles are created using external counter current drive, with additional heating power added afterwards to explore the stability limits and transport properties of the resulting plasmas. The tailored q-profiles are calculated using magnetic equilibrium reconstruction constrained by internal motional Stark effect data to confirm to the presence of the desired helicities. They are then used as a basis for simulations of the transport properties with the gyro-Landau-fluid code TGLF. The simulation results are then compared to the experimentally measured kinetic profiles.

  18. Prediction of the stability of meclofenoxate injection in parenteral admixtures.

    Science.gov (United States)

    Koshiro, A; Fujita, T

    1981-05-01

    A new method for predicting pharmaceutical stability in parenteral admixtures was studied using meclofenoxate hydrochloride injection as a model preparation. The pH and temperature of clinical parenteral admixtures are not constant, unlike experimental buffer solutions, and it is impossible to predict the accurate degradation ratio by the preceding method described by many authors. This study provides a solution to this problem making possible the accurate prediction of degradation ratios of pharmaceuticals even in such complicated systems.

  19. Evolution of liquid holdup profile in a standing protein stabilized foam.

    Science.gov (United States)

    Wang, Zebin; Narsimhan, Ganesan

    2004-12-01

    Evolution of liquid holdup profile in a standing foam formed by whipping and stabilized by sodium caseinate in the presence of xanthan gum when subjected to 16 and 29g centrifugal force fields was measured using magnetic resonance imaging for different pH, ionic strength, protein and xanthan gum concentrations. Drainage resulted in the formation of a separate liquid layer at the bottom at longer times. Foam drainage was slowest at pH 7, lower ionic strength, higher protein and gum concentrations. Foam was found to be most stable at pH 5.1 near the isoelectric point of protein, lower ionic strength and higher protein and xanthan gum concentrations. A predicted equilibrium liquid holdup profile based on a previous model (G. Narsimhan, J. Food Eng. 14 (1991) 139) agreed well with experimental values at sufficiently long times. A proposed model for velocity of drainage of a power law fluid in a Plateau border for two different simplified geometries was incorporated in a previously developed model for foam drainage (G. Narsimhan, J. Food Eng. 14 (1991) 139) to predict the evolution of liquid holdup profiles. The model predictions for simplified circular geometry of Plateau border compared well with the experimental data of liquid holdup profiles at small times. At longer times, however, the predicted liquid holdup profile was larger than the observed, this discrepancy being due to coarsening of bubble size and decrease in foam height not accounted for in the model. A Newtonian model for foam drainage under predicted drainage rates did not agree with the experimental data.

  20. Prediction of Line Voltage Stability Index Using Supervised Learning

    Directory of Open Access Journals (Sweden)

    Ankit Kumar Sharma

    2017-12-01

    Full Text Available In deregulated environment, stability issues have become dominant. Reliability of the power is essential for successful operation of the power system. Often high and dynamic loading conditions present new challenges in terms of decision of the control strategies to the system operator at energy management centre. For the achievement of voltage stability, identification of weak buses is very important. Line stability indices are important predictors of the weak buses in the over loaded system. Identification of the weak buses is the first step of control strategy. This paper presents an effective methodology based on Artificial Neural Network (ANN to predict the Fast Voltage Stability Index (FVSI. Comparative analysis of different topologies of ANN is carried out based on the capability of the prediction of FVSI. Results are validated through offline Newton Raphson (NR simulation method. The proposed methodology is tested over IEEE-14 and IEEE-30 test bus System.

  1. Stability analysis of embedded nonlinear predictor neural generalized predictive controller

    Directory of Open Access Journals (Sweden)

    Hesham F. Abdel Ghaffar

    2014-03-01

    Full Text Available Nonlinear Predictor-Neural Generalized Predictive Controller (NGPC is one of the most advanced control techniques that are used with severe nonlinear processes. In this paper, a hybrid solution from NGPC and Internal Model Principle (IMP is implemented to stabilize nonlinear, non-minimum phase, variable dead time processes under high disturbance values over wide range of operation. Also, the superiority of NGPC over linear predictive controllers, like GPC, is proved for severe nonlinear processes over wide range of operation. The necessary conditions required to stabilize NGPC is derived using Lyapunov stability analysis for nonlinear processes. The NGPC stability conditions and improvement in disturbance suppression are verified by both simulation using Duffing’s nonlinear equation and real-time using continuous stirred tank reactor. Up to our knowledge, the paper offers the first hardware embedded Neural GPC which has been utilized to verify NGPC–IMP improvement in realtime.

  2. A predictable Java profile - rationale and implementations

    DEFF Research Database (Denmark)

    Søndergaard, Hans; Bøgholm, Thomas; Hansen, Rene Rydhof

    2009-01-01

    , and is directly inspired by interactions with the Open Group on their on-going work on a safety critical Java profile (JSR-302). The main contribution is an arrangement of the class hierarchy such that the proposal is a generalization of Real-Time Specification for Java (RTSJ). A further contribution...... is to integrate the mission concept as a handler, such that mission memory becomes a handler private memory and such that mission initialization and finalization are scheduled activities. Two implementations are presented: one directly on an open source JVM using Xenomai and another, based on delegation...

  3. Predicting Academic Success Using Admission Profiles

    Science.gov (United States)

    Davidovitch, Nitza; Soen, Dan

    2015-01-01

    This study, conducted at a tertiary education institution in Israel, following two previous studies, was designed to deal again with a question that is a topic of debate in Israel and worldwide: Is there justification for the approach that considers restrictive university admission policies an efficient tool for predicting students' success at the…

  4. Assessing the Stability and Robustness of Semantic Web Services Recommendation Algorithms Under Profile Injection Attacks

    Directory of Open Access Journals (Sweden)

    GRANDIN, P. H.

    2014-06-01

    Full Text Available Recommendation systems based on collaborative filtering are open by nature, what makes them vulnerable to profile injection attacks that insert biased evaluations in the system database in order to manipulate recommendations. In this paper we evaluate the stability and robustness of collaborative filtering algorithms applied to semantic web services recommendation when submitted to random and segment profile injection attacks. We evaluated four algorithms: (1 IMEAN, that makes predictions using the average of the evaluations received by the target item; (2 UMEAN, that makes predictions using the average of the evaluation made by the target user; (3 an algorithm based on the k-nearest neighbor (k-NN method and (4, an algorithm based on the k-means clustering method.The experiments showed that the UMEAN algorithm is not affected by the attacks and that IMEAN is the most vulnerable of all algorithms tested. Nevertheless, both UMEAN and IMEAN have little practical application due to the low precision of their predictions. Among the algorithms with intermediate tolerance to attacks but with good prediction performance, the algorithm based on k-nn proved to be more robust and stable than the algorithm based on k-means.

  5. Accurate prediction of vaccine stability under real storage conditions and during temperature excursions.

    Science.gov (United States)

    Clénet, Didier

    2018-01-13

    Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed. Copyright © 2018. Published by Elsevier B.V.

  6. Revised prediction (estimation) of Cape Kennedy, Florida, wind speed profile

    Science.gov (United States)

    Guttman, N. B.; Crutcher, H. L.

    1975-01-01

    The prediction of the wind profile maximum speed at Cape Kennedy, Florida, is made for any selected calendar data. The prediction is based on a normal probability distribution model with 15 years of smoothed input data and is static in the sense that no dynamic principles of persistence or synoptic features are considered. Comparison with similar predictions based on 6 years of data shows the same general pattern, but the variability decreased with the increase of sample size.

  7. Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

    Science.gov (United States)

    Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Piatak, David J.; Kvaternik, Raymond G.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

  8. Assist feature printability prediction by 3-D resist profile reconstruction

    Science.gov (United States)

    Zheng, Xin; Huang, Jensheng; Chin, Fook; Kazarian, Aram; Kuo, Chun-Chieh

    2012-06-01

    Sub-resolution Assist Features (SRAFs) are powerful tools to enhance the focus margin of drawn patterns. SRAFs are placed and sized so they do not print on the wafer, but the larger the SRAF, the more effective it becomes at enhancing through-focus stability. The size and location of an SRAF that will image on a wafer is highly dependent upon neighboring patterns and models of SRAF printability are, at present, unreliable. Model-based SRAF placement has been used to enhance resolution at 20nm node processes and below with stringent requirements that inserted SRAFs will not be imaged on wafer. However, despite widespread SRAF use and hard data as to SRAF effectiveness, it has been very difficult to develop a process model that accurately predicts under what process conditions an SRAF will image on a wafer. More accurate models of SRAF printing should allow model based SRAF placement to be relaxed, resulting in more effective SRAF placement and broader focus margins. One of the first problems with the concept of SRAF printability is the definition of an SRAF printing on a wafer. This is not obvious because two different states of printing exist. The first print state is when a residue is left on a wafer from the SRAF. The first state can be considered printing from the point of view that photoresist is on the wafer and the photoresist may even lift off and cause defects. However, the first state can be considered non-printing because the over etch from the etch process will generally remove the photoresist residual and the material underneath. The second state is when a pattern is formed and etched into the substrate, a state at which the pattern has clearly printed on the wafer. Of course, intermediate states may also be defined. In order to be applicable, an SRAF printability model must be able to predict both printing states. In addition, the model must be able to extrapolate to configurations beyond those used to develop the model in the first place. These model

  9. Stability and change in teachers' goal orientation profiles over time : Managerial coaching behavior as a predictor of profile change

    NARCIS (Netherlands)

    Kunst, E.M.; van Woerkom, M.; van Kollenburg, G.H.; Poell, R.F.

    2018-01-01

    Goal orientation is an important predictor of motivation at work. This study introduces goal orientation profiles in the work domain, evaluates their stability over time and assesses the impact of managerial coaching behavior on change in employees' goal orientation profiles. We hypothesize that

  10. First-principles prediction of high-entropy-alloy stability

    Science.gov (United States)

    Feng, Rui; Liaw, Peter K.; Gao, Michael C.; Widom, Michael

    2017-11-01

    High entropy alloys (HEAs) are multicomponent compounds whose high configurational entropy allows them to solidify into a single phase, with a simple crystal lattice structure. Some HEAs exhibit desirable properties, such as high specific strength, ductility, and corrosion resistance, while challenging the scientist to make confident predictions in the face of multiple competing phases. We demonstrate phase stability in the multicomponent alloy system of Cr-Mo-Nb-V, for which some of its binary subsystems are subject to phase separation and complex intermetallic-phase formation. Our first-principles calculation of free energy predicts that the configurational entropy stabilizes a single body-centered cubic (BCC) phase from T = 1700 K up to melting, while precipitation of a complex intermetallic is favored at lower temperatures. We form the compound experimentally and confirm that it develops as a single BCC phase from the melt, but that it transforms reversibly at lower temperatures.

  11. Robust stability in predictive control with soft constraints

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2010-01-01

    constraints. In more detail, we parameterize the MPC predictions in terms of the primary Youla parameter and use this parameter as the online optimization variable. The uncertainty is parameterized in terms of the dual Youla parameter. Stability can then be guaranteed through small gain arguments on the loop...... consisting of the primary and dual Youla parameter. This is included in the MPC optimization as a constraint on the induced gain of the optimization variable. We illustrate the method with a numerical simulation example....

  12. Cognitive and Motivational Profile Shape Predicts Mathematical Skills over and above Profile Level

    Science.gov (United States)

    Reimann, Giselle; Stoecklin, Markus; Lavallee, Kristen; Gut, Janine; Frischknecht, Marie-Claire; Grob, Alexander

    2013-01-01

    The interpretation of subtest profiles from intelligence testing remains popular among many practitioners who use subtest performance to draw diagnostic conclusions, in spite of criticism by some researchers, who point to the low reliability and predictive validity of subtest scores in predicting achievement outcomes. Prior research outlines two…

  13. A machine learns to predict the stability of circumbinary planets

    Science.gov (United States)

    Lam, Christopher; Kipping, David

    2018-01-01

    Long-period circumbinary planets appear to be as common as those orbiting single stars and have been found to frequently have orbital radii just beyond the critical distance for dynamical stability. Assessing the stability is typically done either through N-body simulations or using the classic Holman-Wiegert stability criterion: a second-order polynomial calibrated to broadly match numerical simulations. However, the polynomial is unable to capture islands of instability introduced by mean motion resonances, causing the accuracy of the criterion to approach that of a random coin-toss when close to the boundary. We show how a deep neural network (DNN) trained on N-body simulations generated with REBOUND is able to significantly improve stability predictions for circumbinary planets on initially coplanar, circular orbits. Specifically, we find that the accuracy of our DNN never drops below 86%, even when tightly surrounding the boundary of instability, and is fast enough to be practical for on-the-fly calls during likelihood evaluations typical of modern Bayesian inference. Our binary classifier DNN is made publicly available at https://github.com/CoolWorlds/orbital-stability.

  14. Predicting ecosystem stability from community composition and biodiversity.

    Science.gov (United States)

    de Mazancourt, Claire; Isbell, Forest; Larocque, Allen; Berendse, Frank; De Luca, Enrica; Grace, James B; Haegeman, Bart; Wayne Polley, H; Roscher, Christiane; Schmid, Bernhard; Tilman, David; van Ruijven, Jasper; Weigelt, Alexandra; Wilsey, Brian J; Loreau, Michel

    2013-05-01

    As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species' responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22-75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability. © 2013 Blackwell Publishing Ltd/CNRS.

  15. Predicting Post-Editor Profiles from the Translation Process

    DEFF Research Database (Denmark)

    Singla, Karan; Orrego-Carmona, David; Gonzales, Ashleigh Rhea

    2014-01-01

    The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT...

  16. Prediction of colloidal stability of high concentration protein formulations.

    Science.gov (United States)

    Garidel, Patrick; Blume, Alfred; Wagner, Michael

    2015-05-01

    A major aspect determining the colloidal properties of proteins in solution is the interaction between them and with surrounding molecules. These interactions can be described by the concentration dependency of the protein diffusivity (kD), as derived by dynamic light scattering and was determined for different solutions of monoclonal antibodies varying in pH, ionic strength and presence/absence of co-solute(s). Concerning colloidal stability, protein solutions of different kD values are evaluated, based on their initial solution opalescence, to assess protein association. The current investigation shows that solution conditions with large kD values, indicating high repulsive protein-protein interactions, show lower initial opalescence, compared to solution conditions with low kD values. Upon applying stirring stress, to assess colloidal stability, the trend is such that, the higher kD values are, the more stable the protein solutions are, as long as the thermodynamic and conformational stability is not impaired. Besides, kD allows ranking of solution conditions for highly concentrated immunoglobulin solutions up to concentrations of ∼200 mg mL(-1) with regard to protein self-association and thus opalescent properties. The present study shows that the protein interaction parameter kD can be used as a surrogate parameter for a qualitative prediction of protein association and, thus, colloidal protein stability.

  17. Predicting the stability of surface phases of molybdenum selenides

    Energy Technology Data Exchange (ETDEWEB)

    Roma, Guido [Institut für Anorganische Chemie und Analytische Chemie, Johannes Gutenberg Universität, D-55128, Mainz (Germany); CEA, DEN, Service de Recherches de Métallurgie Physique, F-91191, Gif sur Yvette (France); Ghorbani, Elaheh [Institut für Anorganische Chemie und Analytische Chemie, Johannes Gutenberg Universität, D-55128, Mainz (Germany); IBM Mainz (Germany); Mirhosseini, Hossein; Kühne, Thomas D. [Institut für Anorganische Chemie und Analytische Chemie, Johannes Gutenberg Universität, D-55128, Mainz (Germany); Kiss, Janos; Felser, Claudia [Institut für Anorganische Chemie und Analytische Chemie, Johannes Gutenberg Universität, D-55128, Mainz (Germany); Max Planck Institute for Chemical Physics of Solids, Nöthnitzer Str. 40, D-01187 Dresden (Germany)

    2014-02-10

    The selenization of molybdenum might become an important step in the production of nanostructures based on the layered compound MoSe{sub 2}. It is already technologically relevant for the production of thin film chalcopyrite solar cells. However, the control of the process is still very poor, due to the lack of basic knowledge of the surface thermodynamics of the system. Here, we present a theoretical study on the stability of surface adlayers of Se on the Mo(110) surface, predicting surface patterns and their stability range in terms of temperature and selenium partial pressure. Our results, based on density functional theory, show that the attainable Se coverages range from 1/4 to 3/4 of a monolayer for systems in equilibrium with a gas formed of Se molecules. We provide simulated scanning tunneling microscopy images to help the experimental characterization of adsorbed surface patterns.

  18. Prediction and Stability of Mathematics Skill and Difficulty

    Science.gov (United States)

    Martin, Rebecca B.; Cirino, Paul T.; Barnes, Marcia A.; Ewing-Cobbs, Linda; Fuchs, Lynn S.; Stuebing, Karla K.; Fletcher, Jack M.

    2016-01-01

    The present study evaluated the stability of math learning difficulties over a 2-year period and investigated several factors that might influence this stability (categorical vs. continuous change, liberal vs. conservative cut point, broad vs. specific math assessment); the prediction of math performance over time and by performance level was also evaluated. Participants were 144 students initially identified as having a math difficulty (MD) or no learning difficulty according to low achievement criteria in the spring of Grade 3 or Grade 4. Students were reassessed 2 years later. For both measure types, a similar proportion of students changed whether assessed categorically or continuously. However, categorical change was heavily dependent on distance from the cut point and so more common for MD, who started closer to the cut point; reliable change index change was more similar across groups. There were few differences with regard to severity level of MD on continuous metrics or in terms of prediction. Final math performance on a broad computation measure was predicted by behavioral inattention and working memory while considering initial performance; for a specific fluency measure, working memory was not uniquely related, and behavioral inattention more variably related to final performance, again while considering initial performance. PMID:22392890

  19. Prediction accuracy of soft tissue profile in orthognathic surgery.

    Science.gov (United States)

    Mankad, B; Cisneros, G J; Freeman, K; Eisig, S B

    1999-01-01

    The purpose of this study was to compare soft tissue prediction accuracy of model surgery combined with computer software prediction with that of computer software prediction alone and to assess surgical accuracy by comparing the immediate postsurgical cephalogram with the planned movement of skeletal hard tissue. The predicted and actual soft tissue changes and the corresponding skeletal changes of 16 patients were compared using the Quick Ceph Image cephalometric treatment simulation software. A custom analysis was created to measure the hard tissue and soft tissue changes that occurred as a result of the surgical procedure. On average, the predictions were not significantly different from the actual postsurgical profile changes. Surgical changes of hard tissues from presurgery to postsurgery were accurate as planned except for the position of N-ANS. All lower soft tissue points moved significantly during treatment. Quick Ceph Image offers a rapid and reliable method of profile prediction that does not require artistic skill. If predictions are interpreted with caution and transferred accurately to the model surgery, they can provide an excellent visual aid during presurgical treatment planning and patient presentation.

  20. Template-based quaternary structure prediction of proteins using enhanced profile-profile alignments.

    Science.gov (United States)

    Nakamura, Tsukasa; Oda, Toshiyuki; Fukasawa, Yoshinori; Tomii, Kentaro

    2017-11-27

    Proteins often exist as their multimeric forms when they function as so-called biological assemblies consisting of the specific number and arrangement of protein subunits. Consequently, elucidating biological assemblies is necessary to improve understanding of protein function. Template-Based Modeling (TBM), based on known protein structures, has been used widely for protein structure prediction. Actually, TBM has become an increasingly useful approach in recent years because of the increased amounts of information related to protein amino acid sequences and three-dimensional structures. An apparently similar situation exists for biological assembly structure prediction as protein complex structures in the PDB increase, although the inference of biological assemblies is not a trivial task. Many methods using TBM, including ours, have been developed for protein structure prediction. Using enhanced profile-profile alignments, we participated in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12), as the FONT team (Group # 480). Herein, we present experimental procedures and results of retrospective analyses using our approach for the Quaternary Structure Prediction category of CASP12. We performed profile-profile alignments of several types, based on FORTE, our profile-profile alignment algorithm, to identify suitable templates. Results show that these alignment results enable us to find templates in almost all possible cases. Moreover, we have come to understand the necessity of developing a model selection method that provides improved accuracy. Results also demonstrate that, to some extent, finding templates of protein complexes is useful even for MEDIUM and HARD assembly prediction. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

  1. A Toolbox for Predicting G-Quadruplex Formation and Stability

    Directory of Open Access Journals (Sweden)

    Han Min Wong

    2010-01-01

    Full Text Available G-quadruplexes are four stranded nucleic acid structures formed around a core of guanines, arranged in squares with mutual hydrogen bonding. Many of these structures are highly thermally stable, especially in the presence of monovalent cations, such as those found under physiological conditions. Understanding of their physiological roles is expanding rapidly, and they have been implicated in regulating gene transcription and translation among other functions. We have built a community-focused website to act as a repository for the information that is now being developed. At its core, this site has a detailed database (QuadDB of predicted G-quadruplexes in the human and other genomes, together with the predictive algorithm used to identify them. We also provide a QuadPredict server, which predicts thermal stability and acts as a repository for experimental data from all researchers. There are also a number of other data sources with computational predictions. We anticipate that the wide availability of this information will be of use both to researchers already active in this exciting field and to those who wish to investigate a particular gene hypothesis.

  2. Robust stability in constrained predictive control through the Youla parameterisations

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2011-01-01

    In this article we take advantage of the primary and dual Youla parameterisations to set up a soft constrained model predictive control (MPC) scheme. In this framework it is possible to guarantee stability in face of norm-bounded uncertainties. Under special conditions guarantees are also given f...... arguments on the loop consisting of the primary and dual Youla parameter. This is included in the MPC optimisation as a constraint on the induced gain of the optimisation variable. We illustrate the method with a numerical simulation example....

  3. In silico pKa prediction and ADME profiling.

    Science.gov (United States)

    Cruciani, Gabriele; Milletti, Francesca; Storchi, Loriano; Sforna, Gianluca; Goracci, Laura

    2009-11-01

    Improving the ADME profile of drug candidates is a critical step in lead optimization, and because pKa affects most ADME properties such as lipophilicity, solubility, and metabolism, it is extremely advantageous to predict pKa in order to guide the design of new compounds. However, accurately (designed for computational and medicinal chemists to predict the pKa values of organic compounds. Here, we present the major issues considered when we developed MoKa, such as the accurate selection of training data, the fundamentals of the methodology (which has also been extended to predict protein pKa), the treatment of multiprotic compounds, and the selection of the dominant tautomer for the calculation. Last, we illustrate some specific applications of MoKa to predict solubility, lipophilicity, and metabolism.

  4. Bayesian prediction of RNA translation from ribosome profiling.

    Science.gov (United States)

    Malone, Brandon; Atanassov, Ilian; Aeschimann, Florian; Li, Xinping; Großhans, Helge; Dieterich, Christoph

    2017-04-07

    Ribosome profiling via high-throughput sequencing (ribo-seq) is a promising new technique for characterizing the occupancy of ribosomes on messenger RNA (mRNA) at base-pair resolution. The ribosome is responsible for translating mRNA into proteins, so information about its occupancy offers a detailed view of ribosome density and position which could be used to discover new translated open reading frames (ORFs), among other things. In this work, we propose Rp-Bp, an unsupervised Bayesian approach to predict translated ORFs from ribosome profiles. We use state-of-the-art Markov chain Monte Carlo techniques to estimate posterior distributions of the likelihood of translation of each ORF. Hence, an important feature of Rp-Bp is its ability to incorporate and propagate uncertainty in the prediction process. A second novel contribution is automatic Bayesian selection of read lengths and ribosome P-site offsets (BPPS). We empirically demonstrate that our read length selection technique modestly improves sensitivity by identifying more canonical and non-canonical ORFs. Proteomics- and quantitative translation initiation sequencing-based validation verifies the high quality of all of the predictions. Experimental comparison shows that Rp-Bp results in more peptide identifications and proteomics-validated ORF predictions compared to another recent tool for translation prediction. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Long-Term Profile Stability of the Kuder Occupational Interest Survey

    Science.gov (United States)

    Zytowski, Donald G.

    1976-01-01

    Profile stability of the Kuder Occupational Interest Survey was assessed for profiles obtained twelve and nineteen years apart for persons between thirteen and twenty years of age at the time of first administration. Reported reliabilities ranged from .40 to .80 for various sub-samples. (JKS)

  6. Toddlers' Temperament Profiles: Stability and Relations to Negative and Positive Parenting

    Science.gov (United States)

    van den Akker, Alithe L.; Dekovic, Maja; Prinzie, Peter; Asscher, Jessica J.

    2010-01-01

    This study investigated the type and stability of temperament profiles in toddlers, and relations of profile probability to negative and positive parenting trajectories. Mothers (N = 96) rated their child's (41 girls and 54 boys) Sociability, Anger Proneness, and Activity Level four times during 1 year. The assessment of parenting included both…

  7. Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Liying Yang

    2016-01-01

    Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

  8. Phase stabilization in cinnarizine complexes using X-ray profile ...

    Indian Academy of Sciences (India)

    Abstract. Characterization of cobalt(II), cadmium(II), copper(II) and tin(II) cinnarizine complexes have been carried out using conductivity, electronic spectra, infrared, nmr, thermogravimetric and X- ray analyses to establish the nature of phase stabilization in these materials. Also, the intrinsic strain components present in ...

  9. Phase stabilization in cinnarizine complexes using X-ray profile ...

    Indian Academy of Sciences (India)

    Characterization of cobalt(II), cadmium(II), copper(II) and tin(II) cinnarizine complexes have been carried out using conductivity, electronic spectra, infrared, nmr, thermogravimetric and Xray analyses to establish the nature of phase stabilization in these materials. Also, the intrinsic strain components present in these ...

  10. Pore pressure prediction and well bore stability analysis in Lower Paleozoic shale formation, N Poland

    Science.gov (United States)

    Słota-Valim, Małgorzata

    2017-04-01

    Pore pressure and wellbore stability sometimes pose a serious challenge while drilling, especially through rock formations of reduced strength or through intervals where abnormally high pore pressure was formed. Lack of prediction of pore pressure and lack of wellbore stability analysis introduce an element of uncertainty in selection of drilling fluid density. Too low density of drilling fluid can lead to uncontrolled flow of the reservoir fluid to the wellbore (kicks), washouts and occurrence of cavern like structures called breakouts. On the other hand too high density can lead to formation fracturing and further fluid loss. Therefore wellbore stability loss frequently prolongs the operating time, rising the costs of the drilling and in severe cases may end up well abandons loss. The above mentioned complications can be avoided or greatly reduced by reliable analysis of drilling conditions with the aspects to geomechanical characteristics of drilled rock formations. This study presents the results of analysis of pore pressure performed with the use of commonly used in oil industry methods. The analysis of pore pressure was carried out in almost entire profile of four boreholes drilled through lower Paleozoic shales, deposited in the southern part of the Baltic Basin. In addition wellbore stability analysis was performed in the well with most complete geomechanical input data base. Obtained results helped identifying intervals with elevated pore pressure could pose a risk during drilling operation. Elaborated 1D geomechanical model provides safe mud weight window helping to reduce the instabilities risk and constitute a great tool for geomechanical model validation.

  11. Persistent homology for the quantitative prediction of fullerene stability.

    Science.gov (United States)

    Xia, Kelin; Feng, Xin; Tong, Yiying; Wei, Guo Wei

    2015-03-05

    Persistent homology is a relatively new tool often used for qualitative analysis of intrinsic topological features in images and data originated from scientific and engineering applications. In this article, we report novel quantitative predictions of the energy and stability of fullerene molecules, the very first attempt in using persistent homology in this context. The ground-state structures of a series of small fullerene molecules are first investigated with the standard Vietoris-Rips complex. We decipher all the barcodes, including both short-lived local bars and long-lived global bars arising from topological invariants, and associate them with fullerene structural details. Using accumulated bar lengths, we build quantitative models to correlate local and global Betti-2 bars, respectively with the heat of formation and total curvature energies of fullerenes. It is found that the heat of formation energy is related to the local hexagonal cavities of small fullerenes, while the total curvature energies of fullerene isomers are associated with their sphericities, which are measured by the lengths of their long-lived Betti-2 bars. Excellent correlation coefficients (>0.94) between persistent homology predictions and those of quantum or curvature analysis have been observed. A correlation matrix based filtration is introduced to further verify our findings. © 2014 Wiley Periodicals, Inc.

  12. Persistent Homology for The Quantitative Prediction of Fullerene Stability

    Science.gov (United States)

    Xia, Kelin; Feng, Xin; Tong, Yiying; Wei, Guo Wei

    2014-01-01

    Persistent homology is a relatively new tool often used for qualitative analysis of intrinsic topological features in images and data originated from scientific and engineering applications. In this paper, we report novel quantitative predictions of the energy and stability of fullerene molecules, the very first attempt in employing persistent homology in this context. The ground-state structures of a series of small fullerene molecules are first investigated with the standard Vietoris-Rips complex. We decipher all the barcodes, including both short-lived local bars and long-lived global bars arising from topological invariants, and associate them with fullerene structural details. By using accumulated bar lengths, we build quantitative models to correlate local and global Betti-2 bars respectively with the heat of formation and total curvature energies of fullerenes. It is found that the heat of formation energy is related to the local hexagonal cavities of small fullerenes, while the total curvature energies of fullerene isomers are associated with their sphericities, which are measured by the lengths of their long-lived Betti-2 bars. Excellent correlation coefficients (> 0.94) between persistent homology predictions and those of quantum or curvature analysis have been observed. A correlation matrix based filtration is introduced to further verify our findings. PMID:25523342

  13. Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

    2016-11-11

    Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

  14. Genetic profiling to predict recurrence of early cervical cancer.

    Science.gov (United States)

    Lee, Yoo-Young; Kim, Tae-Joong; Kim, Ji-Young; Choi, Chel Hun; Do, In-Gu; Song, Sang Yong; Sohn, Insuk; Jung, Sin-Ho; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Byoung-Gie

    2013-12-01

    Recurrence is the major cause of death in early cervical cancer. We compared the prediction powers for disease recurrence between the gene set prognostic model and the clinical prognostic model. A gene set model to predict disease free survival was developed using the cDNA-mediated annealing, selection, extension, and ligation (DASL) assay data set from a cohort of early cervical cancer patients who had been treated with radical surgery with or without adjuvant therapy. A clinical prediction model was also developed using the same cohort, and the ability of predicting recurrence from each model was compared. Adequate DASL assay profiles were obtained from 300 patients, and we selected 12 genes for the gene set model. When patients were categorized as having a low or high risk by the prognostic score, the Kaplan-Meier curve showed significantly different recurrence rates between the two groups. The clinical model was developed using FIGO stage and post-surgical pathological findings. In multivariate Cox regression analysis of prognostic models, the gene set prognostic model showed a higher hazard ratio than that of the clinical prognostic model. The genetic quantitative approach may be better in predicting recurrence in early cervical cancer patients. © 2013 Elsevier Inc. All rights reserved.

  15. Navier-Stokes Predictions of Dynamic Stability Derivatives: Evaluation of Steady-State Methods

    National Research Council Canada - National Science Library

    DeSpirito, James; Silton, Sidra I; Weinacht, Paul

    2008-01-01

    The prediction of the dynamic stability derivatives-roll-damping, Magnus, and pitch-damping moments-were evaluated for three spin-stabilized projectiles using steady-state computational fluid dynamic (CFD) calculations...

  16. Prediction of propagated wave profiles based on point measurement

    Directory of Open Access Journals (Sweden)

    Sang-Beom Lee

    2014-03-01

    Full Text Available This study presents the prediction of propagated wave profiles using the wave information at a fixed point. The fixed points can be fixed in either space or time. Wave information based on the linear wave theory can be expressed by Fredholm integral equation of the first kinds. The discretized matrix equation is usually an ill-conditioned system. Tikhonov regularization was applied to the ill-conditioned system to overcome instability of the system. The regularization parameter is calculated by using the L-curve method. The numerical results are compared with the experimental results. The analysis of the numerical computation shows that the Tikhonov regularization method is useful.

  17. Predicting At-Risk Patient Profiles from Big Prescription Data

    OpenAIRE

    Genevès, Pierre; Calmant, Thomas; Layaïda, Nabil; Lepelley, Marion; Artemova, Svetlana; Bosson, Jean-Luc

    2017-01-01

    We show how the analysis of very large amounts of drug prescription data make it possible to detect, on the day of hospital admission, patients at risk of developing complications during their hospital stay. We explore, for the first time, to which extent volume and variety of big prescription data help in constructing predictive models for the automatic detection of at-risk profiles.Our methodology is designed to validate our claims that: (1) drug prescription data on the day of admission co...

  18. Acylcarnitines profile best predicts survival in horses with atypical myopathy.

    Directory of Open Access Journals (Sweden)

    François Boemer

    Full Text Available Equine atypical myopathy (AM is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups.

  19. EFFECT OF PROFILES AND SHAPE ON IDEAL STABILITY OF ADVANCED TOKAMAK EQUILIBRIA

    Energy Technology Data Exchange (ETDEWEB)

    MAKOWSKI,MA; CASPER,TA; FERRON,JR; TAYLOR,TS; TURNBULL,AD

    2003-08-01

    OAK-B135 The pressure profile and plasma shape, parameterized by elongation ({kappa}), triangularity ({delta}), and squareness ({zeta}), strongly influence stability. In this study, ideal stability of single null and symmetric, double-null, advanced tokamak (AT) configurations is examined. All the various shapes are bounded by a common envelope and can be realized in the DIII-D tokamak. The calculated AT equilibria are characterized by P{sub 0}/

    {approx} 2.0-4.5, weak negative central shear, high q{sub min} (> 2.0), high bootstrap fraction, an H-mode pedestal, and varying shape parameters. The pressure profile is modeled by various polynomials together with a hyperbolic tangent pedestal, consistent with experimental observations. Stability is calculated with the DCON code and the resulting stability boundary is corroborated by GATO runs.

  20. Effect of Profiles and Space on Ideal Stability of Advanced Tokamak Equilibria

    Energy Technology Data Exchange (ETDEWEB)

    Makowski, M A; Casper, T A; Ferron, J R; Taylor, T S; Turnbull, A D

    2003-07-07

    The pressure profile and plasma shape, parameterized by elongation ({kappa}), triangularity ({delta}), and squareness ({zeta}), strongly influence stability. In this study, ideal stability of single null and symmetric, double-null, advanced tokamak (AT) configurations is examined. All the various shapes are bounded by a common envelope and can be realized in the DIII-D tokamak. The calculated AT equilibria are characterized by P{sub 0}/{l_angle}P{r_brace} {approx} 2.0-4.5, weak negative central shear, high q{sub min} (>2.0), high bootstrap fraction, an H-mode pedestal, and varying shape parameters. The pressure profile is modeled by various polynomials together with a hyperbolic tangent pedestal, consistent with experimental observations. Stability is calculated with the DCON code and the resulting stability boundary is corroborated by GATO runs.

  1. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis

    Science.gov (United States)

    Sweeney, Shannon R; Kavanaugh, Arthur; Lodi, Alessia; Wang, Bo; Boyle, David; Tiziani, Stefano; Guma, Monica

    2016-01-01

    Objective: To determine whether characterisation of patients' metabolic profiles, utilising nuclear magnetic resonance (NMR) and mass spectrometry (MS), could predict response to rituximab therapy. 23 patients with active, seropositive rheumatoid arthritis (RA) on concomitant methotrexate were treated with rituximab. Patients were grouped into responders and non-responders according to the American College of Rheumatology improvement criteria, at a 20% level at 6 months. A Bruker Avance 700 MHz spectrometer and a Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometer were used to acquire 1H-NMR and ultra high pressure liquid chromatography (UPLC)–MS/MS spectra, respectively, of serum samples before and after rituximab therapy. Data processing and statistical analysis were performed in MATLAB. 14 patients were characterised as responders, and 9 patients were considered non-responders. 7 polar metabolites (phenylalanine, 2-hydroxyvalerate, succinate, choline, glycine, acetoacetate and tyrosine) and 15 lipid species were different between responders and non-responders at baseline. Phosphatidylethanolamines, phosphatidyserines and phosphatidylglycerols were downregulated in responders. An opposite trend was observed in phosphatidylinositols. At 6 months, 5 polar metabolites (succinate, taurine, lactate, pyruvate and aspartate) and 37 lipids were different between groups. The relationship between serum metabolic profiles and clinical response to rituximab suggests that 1H-NMR and UPLC–MS/MS may be promising tools for predicting response to rituximab. PMID:27651926

  2. Computational lipidology: predicting lipoprotein density profiles in human blood plasma.

    Directory of Open Access Journals (Sweden)

    Katrin Hübner

    2008-05-01

    Full Text Available Monitoring cholesterol levels is strongly recommended to identify patients at risk for myocardial infarction. However, clinical markers beyond "bad" and "good" cholesterol are needed to precisely predict individual lipid disorders. Our work contributes to this aim by bringing together experiment and theory. We developed a novel computer-based model of the human plasma lipoprotein metabolism in order to simulate the blood lipid levels in high resolution. Instead of focusing on a few conventionally used predefined lipoprotein density classes (LDL, HDL, we consider the entire protein and lipid composition spectrum of individual lipoprotein complexes. Subsequently, their distribution over density (which equals the lipoprotein profile is calculated. As our main results, we (i successfully reproduced clinically measured lipoprotein profiles of healthy subjects; (ii assigned lipoproteins to narrow density classes, named high-resolution density sub-fractions (hrDS, revealing heterogeneous lipoprotein distributions within the major lipoprotein classes; and (iii present model-based predictions of changes in the lipoprotein distribution elicited by disorders in underlying molecular processes. In its present state, the model offers a platform for many future applications aimed at understanding the reasons for inter-individual variability, identifying new sub-fractions of potential clinical relevance and a patient-oriented diagnosis of the potential molecular causes for individual dyslipidemia.

  3. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis.

    Science.gov (United States)

    Sweeney, Shannon R; Kavanaugh, Arthur; Lodi, Alessia; Wang, Bo; Boyle, David; Tiziani, Stefano; Guma, Monica

    2016-01-01

    To determine whether characterisation of patients' metabolic profiles, utilising nuclear magnetic resonance (NMR) and mass spectrometry (MS), could predict response to rituximab therapy. 23 patients with active, seropositive rheumatoid arthritis (RA) on concomitant methotrexate were treated with rituximab. Patients were grouped into responders and non-responders according to the American College of Rheumatology improvement criteria, at a 20% level at 6 months. A Bruker Avance 700 MHz spectrometer and a Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometer were used to acquire (1)H-NMR and ultra high pressure liquid chromatography (UPLC)-MS/MS spectra, respectively, of serum samples before and after rituximab therapy. Data processing and statistical analysis were performed in MATLAB. 14 patients were characterised as responders, and 9 patients were considered non-responders. 7 polar metabolites (phenylalanine, 2-hydroxyvalerate, succinate, choline, glycine, acetoacetate and tyrosine) and 15 lipid species were different between responders and non-responders at baseline. Phosphatidylethanolamines, phosphatidyserines and phosphatidylglycerols were downregulated in responders. An opposite trend was observed in phosphatidylinositols. At 6 months, 5 polar metabolites (succinate, taurine, lactate, pyruvate and aspartate) and 37 lipids were different between groups. The relationship between serum metabolic profiles and clinical response to rituximab suggests that (1)H-NMR and UPLC-MS/MS may be promising tools for predicting response to rituximab.

  4. New Theoretical Technique Developed for Predicting the Stability of Alloys

    Science.gov (United States)

    1996-01-01

    When alloys are being designed for aeronautical and other applications, a substantial experimental effort is necessary to make incremental changes in the desired alloy properties. A scheme to narrow the field to the most promising candidates would substantially reduce the high cost of this experimental screening. Such a method for determining alloy properties, called the BFS (Bozzolo, Ferrante, and Smith) method, has been developed at the NASA Lewis Research Center. This method was used to calculate the thermal stability and mechanical strength of 200 alloys of Ni3Al, with Cu and Au impurities forming ternary and quaternary compounds. With recent advances in the method, almost any metallic impurity and crystal structure can be addressed. In addition, thermal effects can be addressed with Monte Carlo techniques. At present, an experimental program is in progress to verify these results. The method identified a small number of the most promising candidates from the 200 alloys with the largest negative heat of formation and the highest bulk modulus. This calculation required only 5 min of CPU time on a VAX computer. It is clear that semi-empirical methods have achieved the level of development and reliability to warrant examining this new approach to the problem of alloy design. The present work was meant to demonstrate, perhaps in a rather simple way, this power. This type of application of atomistic simulation methods can narrow the gap and improve the feedback between theoretical predictions and laboratory experimentation.

  5. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  6. Gene expression profiling predicts survival in conventional renal cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Hongjuan Zhao

    2006-01-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  7. Constructing Prediction Models from Expression Profiles for Large Scale lncRNA-miRNA Interaction Profiling.

    Science.gov (United States)

    Huang, Yu-An; Chan, Keith C C; You, Zhu-Hong

    2017-10-23

    The interaction of miRNA and lncRNA is known to be important for gene regulations. However, not many computational approaches have been developed to analyse known interactions and predict the unknown ones. Given that there are now more evidences that suggest that lncRNA-miRNA interactions are closely related to their relative expression levels in the form of a titration mechanism, we analyzed the patterns in large-scale expression profiles of known lncRNA-miRNA interactions. From these uncovered patterns, we noticed that lncRNAs tend to interact collaboratively with miRNAs of similar expression profiles, and vice versa. By representing known interaction between lncRNA and miRNA as a bipartite graph, we propose here a technique, called EPLMI, to construct a prediction model from such a graph. EPLMI performs its tasks based on the assumption that lncRNAs that are highly similar to each other tend to have similar interaction or non-interaction patterns with miRNAs and vice versa. The effectiveness of the prediction model so constructed has been evaluated using the latest dataset of lncRNA-miRNA interactions. The results show that the prediction model can achieve AUCs of 0.8522 and 0.8447±0.0017 based on LOOCV and 5-fold cross validation. Using this model, we show that lncRNA-miRNA interactions can be reliably predicted. We also show that we can use it to select the most likely lncRNA targets that specific miRNAs would interact with. We believe that the prediction models discovered by EPLMI can yield great insights for further research on ceRNA regulation network. To the best of our knowledge, EPLMI is the first technique that is developed for large-scale lncRNA-miRNA interaction profiling. Matlab codes and dataset are available at https://github.com/yahuang1991polyu/EPLMI/. yu-an.huang@connect.polyu.hk. Supplementary data are available at Bioinformatics online.

  8. Benchmarking and qualification of the NUFREQ-NPW code for best estimate prediction of multi-channel core stability margins

    Energy Technology Data Exchange (ETDEWEB)

    Taleyarkhan, R.; Lahey, R.T. Jr.; McFarlane, A.F.; Podowski, M.Z.

    1988-01-01

    The NUFREQ-NPW code was modified and set up at Westinghouse, USA for mixed fuel type multi-channel core-wide stability analysis. The resulting code, NUFREQ-NPW, allows for variable axial power profiles between channel groups and can handle mixed fuel types. Various models incorporated into NUFREQ-NPW were systematically compared against the Westinghouse channel stability analysis code MAZDA-NF, for which the mathematical model was developed, in an entirely different manner. Excellent agreement was obtained which verified the thermal-hydraulic modeling and coding aspects. Detailed comparisons were also performed against nuclear-coupled reactor core stability data. All thirteen Peach Bottom-2 EOC-2/3 low flow stability tests were simulated. A key aspect for code qualification involved the development of a physically based empirical algorithm to correct for the effect of core inlet flow development on subcooled boiling. Various other modeling assumptions were tested and sensitivity studies performed. Good agreement was obtained between NUFREQ-NPW predictions and data. Moreover, predictions were generally on the conservative side. The results of detailed direct comparisons with experimental data using the NUFREQ-NPW code; have demonstrated that BWR core stability margins are conservatively predicted, and all data trends are captured with good accuracy. The methodology is thus suitable for BWR design and licensing purposes. 11 refs., 12 figs., 2 tabs.

  9. Stability and relative validity of the Neuromuscular Disease Impact Profile (NMDIP)

    NARCIS (Netherlands)

    Bos, Isaac; Kuks, Jan B. M.; Almansa, Josue; Kremer, Hubertus P. H.; Wynia, Klaske

    2017-01-01

    Background: The aim of this study was to examine the stability and relative validity (RV) of the Neuromuscular Disease Impact Profile (NMDIP) using criterion-related groups. In a previous study the NMDIP-scales showed good internal consistency, convergent and discriminant validity. Known-groups

  10. National Profiles of School Readiness Skills for Head Start Children: An Investigation of Stability and Change

    Science.gov (United States)

    McWayne, Christine M.; Hahs-Vaughn, Debbie L.; Cheung, Katherine; Wright, Linnie E. Green

    2012-01-01

    Among a nationally representative sample of 2336 Head Start children, patterns of school readiness were compared at the beginning and end of children's first preschool year, and predictors of stability and change across readiness profiles were examined. The present study documented that although the majority of children remain in a qualitatively…

  11. Stability of Language and Literacy Profiles of Children with Language Impairment in the Public Schools

    Science.gov (United States)

    Tambyraja, Sherine R.; Schmitt, Mary Beth; Farquharson, Kelly; Justice, Laura M.

    2015-01-01

    Purpose: The present study focused on the identification and stability of language and literacy profiles of primary school children receiving school-based language therapy over the course of one academic year. Method: Participants included 272 early elementary school-age children (144 boys, 128 girls) who had been clinically identified as having a…

  12. Is primary stability a predictable parameter for loading implant?

    Directory of Open Access Journals (Sweden)

    Ratnadeep Patil

    2016-01-01

    Full Text Available Implant stability is important for osseointregration; without it, long-term success cannot be achieved. Continuous monitoring in a quantitative and objective manner is important to determine the status of implant stability. Measurement of implant stability is a valuable tool for making decisions pertaining to treatment protocol and it also improves dentist-patient communication. Owing to the invasive nature of histological analysis, various others methods have been proposed such as radiographs, cutting torque resistance, reverse torque, and resonance frequency analysis (RFA. This review focuses on the objectives and various methods to evaluate implant stability.

  13. Prediction of propagated wave profiles based on point measurement

    Directory of Open Access Journals (Sweden)

    Lee Sang-Beom

    2014-03-01

    Full Text Available This study presents the prediction of propagated wave profiles using the wave information at a fixed point. The fixed points can be fixed in either space or time. Wave information based on the linear wave theory can be expressed by Fredholm integral equation of the first kinds. The discretized matrix equation is usually an ill-conditioned system. Tikhonov regularization was applied to the ill-conditioned system to overcome instability of the system. The regularization parameter is calculated by using the L-curve method. The numerical results are compared with the expe¬rimental results. The analysis of the numerical computation shows that the Tikhonov regularization method is useful.

  14. Gene-expression profiling to predict responsiveness to immunotherapy.

    Science.gov (United States)

    Jamieson, N B; Maker, A V

    2017-03-01

    Recent clinical successes with immunotherapy have resulted in expanding indications for cancer therapy. To enhance antitumor immune responses, and to better choose specific strategies matched to patient and tumor characteristics, genomic-driven precision immunotherapy will be necessary. Herein, we explore the role that tumor gene-expression profiling (GEP) may have in the prediction of an immunotherapeutic response. Genetic markers associated with response to immunotherapy are addressed as they pertain to the tumor genomic landscape, the extent of DNA damage, tumor mutational load and tumor-specific neoantigens. Furthermore, genetic markers associated with resistance to checkpoint blockade and relapse are reviewed. Finally, the utility of GEP to identify new tumor types for immunotherapy and implications for combinatorial strategies are summarized.

  15. Longitudinal stability of pre-reading skill profiles of kindergarten children: implications for early screening and theories of reading.

    Science.gov (United States)

    Ozernov-Palchik, Ola; Norton, Elizabeth S; Sideridis, Georgios; Beach, Sara D; Wolf, Maryanne; Gabrieli, John D E; Gaab, Nadine

    2017-09-01

    Research suggests that early identification of developmental dyslexia is important for mitigating the negative effects of dyslexia, including reduced educational attainment and increased socioemotional difficulties. The strongest pre-literacy predictors of dyslexia are rapid automatized naming (RAN), phonological awareness (PA), letter knowledge, and verbal short-term memory. The relationship among these constructs has been debated, and several theories have emerged to explain the unique role of each in reading ability/disability. Furthermore, the stability of identification of risk based on these measures varies widely across studies, due in part to the different cut-offs employed to designate risk. We applied a latent profile analysis technique with a diverse sample of 1215 kindergarten and pre-kindergarten students from 20 schools, to investigate whether PA, RAN, letter knowledge, and verbal short-term memory measures differentiated between homogenous profiles of performance on these measures. Six profiles of performance emerged from the data: average performers, below average performers, high performers, PA risk, RAN risk, and double-deficit risk (both PA and RAN). A latent class regression model was employed to investigate the longitudinal stability of these groups in a representative subset of children (n = 95) nearly two years later, at the end of 1st grade. Profile membership in the spring semester of pre-kindergarten or fall semester of kindergarten was significantly predictive of later reading performance, with the specific patterns of performance on the different constructs remaining stable across the years. There was a higher frequency of PA and RAN deficits in children from lower socioeconomic status (SES) backgrounds. There was no evidence for the IQ-achievement discrepancy criterion traditionally used to diagnose dyslexia. Our results support the feasibility of early identification of dyslexia risk and point to the heterogeneity of risk profiles

  16. The Reliability and Predictive Validity of the Stalking Risk Profile.

    Science.gov (United States)

    McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

    2018-03-01

    This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period ( Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

  17. Insulin Resistance Predicts Atherogenic Lipoprotein Profile in Nondiabetic Subjects

    Directory of Open Access Journals (Sweden)

    Flávia De C. Cartolano

    2017-01-01

    Full Text Available Background. Atherogenic diabetes is associated with an increased cardiovascular risk and mortality in diabetic individuals; however, the impact of insulin resistance (IR in lipid metabolism in preclinical stages is generally underreported. For that, we evaluated the capacity of IR to predict an atherogenic lipid subfraction profile. Methods. Complete clinical evaluation and biochemical analysis (lipid, glucose profile, LDL, and HDL subfractions and LDL phenotype and size were performed in 181 patients. The impact of IR as a predictor of atherogenic lipoproteins was tested by logistic regression analysis in raw and adjusted models. Results. HDL-C and Apo AI were significantly lower in individuals with IR. Individuals with IR had a higher percentage of small HDL particles, lower percentage in the larger ones, and reduced frequency of phenotype A (IR = 62%; non-IR = 83%. IR individuals had reduced probability to have large HDL (OR = 0.213; CI = 0.999–0.457 and had twice more chances to show increased small HDL (OR = 2.486; CI = 1.341–7.051. IR was a significant predictor of small LDL (OR = 3.075; CI = 1.341–7.051 and atherogenic phenotype (OR = 3.176; CI = 1.469–6.867. Conclusion. IR, previously DM2 diagnosis, is a strong predictor of quantitative and qualitative features of lipoproteins directly associated with an increased atherogenic risk.

  18. Biotransformation and in vivo stability of protein biotherapeutics: impact on candidate selection and pharmacokinetic profiling.

    Science.gov (United States)

    Hall, Michael P

    2014-11-01

    Historically, since the metabolism of administered peptide/protein drugs ("biotherapeutics") has been expected to undergo predictable pathways similar to endogenous proteins, comprehensive biotherapeutic metabolism studies have not been widely reported in the literature. However, since biotherapeutics have rapidly evolved into an impressive array of eclectic modalities, there has been a shift toward understanding the impact of metabolism on biotherapeutic development. For biotherapeutics containing non-native chemical linkers and other moieties besides natural amino acids, metabolism studies are critical as these moieties may impart undesired toxicology. For biotherapeutics that are composed solely of natural amino acids, where end-stage peptide and amino acid catabolites do not generally pose toxicity concerns, the understanding of biotherapeutic biotransformation, defined as in vivo modifications such as peripherally generated intermediate circulating catabolites prior to end-stage degradation or elimination, may impact in vivo stability and potency/clearance. As of yet, there are no harmonized methodologies for understanding biotherapeutic biotransformation and its impact on drug development, nor is there clear guidance from regulatory agencies on how and when these studies should be conducted. This review provides an update on biotherapeutic biotransformation studies and an overview of lessons learned, tools that have been developed, and suggestions of approaches to address issues. Biotherapeutic biotransformation studies, especially for certain modalities, should be implemented at an early stage of development to 1) understand the impact on potency/clearance, 2) select the most stable candidates or direct protein re-engineering efforts, and 3) select the best bioanalytical technique(s) for proper drug quantification and subsequent pharmacokinetic profiling and exposure/response assessment. Copyright © 2014 by The American Society for Pharmacology and

  19. Spectral stability of undercompressive shock profile solutions of a modified KdV-Burgers equation

    Directory of Open Access Journals (Sweden)

    Jeff Dodd

    2007-10-01

    Full Text Available It is shown that certain undercompressive shock profile solutions of the modified Korteweg-de Vries-Burgers equation $$ partial_t u + partial_x(u^3 = partial_x^3 u + alpha partial_x^2 u, quad alpha geq 0 $$ are spectrally stable when $alpha$ is sufficiently small, in the sense that their linearized perturbation equations admit no eigenvalues having positive real part except a simple eigenvalue of zero (due to the translation invariance of the linearized perturbation equations. This spectral stability makes it possible to apply a theory of Howard and Zumbrun to immediately deduce the asymptotic orbital stability of these undercompressive shock profiles when $alpha$ is sufficiently small and positive.

  20. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

    Directory of Open Access Journals (Sweden)

    Camille Jeunet

    Full Text Available Mental-Imagery based Brain-Computer Interfaces (MI-BCIs allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG, which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

  1. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

    Science.gov (United States)

    Jeunet, Camille; N'Kaoua, Bernard; Subramanian, Sriram; Hachet, Martin; Lotte, Fabien

    2015-01-01

    Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

  2. Accurate Stabilities of Laccase Mutants Predicted with a Modified FoldX Protocol

    DEFF Research Database (Denmark)

    Christensen, Niels Johan; Kepp, Kasper Planeta

    2012-01-01

    Fungal laccases are multi-copper enzymes of industrial importance due to their high stability, multi-functionality, and oxidizing power. This paper reports computational protocols that quantify the relative stability (∆∆G of folding) of mutants of high-redox-potential laccases (TvLIIIb and PM1L) ...... forces governing the high stability of fungal laccases, most notably the hydrophobic and Van der Waal's interactions in the folded state, which provide most of the predictive power....

  3. Ankle and knee flexibility and strength predict dynamic postural stability during single-leg jump landings

    OpenAIRE

    Williams, VJ; Nagai, T; Sell, TC; Abt, JP; Rowe, RS; McGrail, MA; Lephart, SM

    2016-01-01

    Dynamic postural stability is important for injury prevention, but little is known about how lower-extremity musculoskeletal characteristics (range of motion [ROM] and strength) contribute to dynamic postural stability. Knowing which modifiable physical characteristics predict dynamic postural stability can help direct rehabilitation and injury-prevention programs. Objective: To determine if trunk, hip, knee, and ankle flexibility and strength variables are significant predictors of dynamic p...

  4. Prediction of the biochar carbon stability by thermal analysis

    Science.gov (United States)

    Méndez, Ana; Cely, Paola; Plaza, César; Paz-Ferreiro, Jorge; Gascó, Gabriel

    2015-04-01

    Thermal analysis (DTA, DSC, TG and dTG) has been used for decades to characterize carbonaceous materials used as fuels (oil, coal). Our research group has used these techniques for the characterisation of different biochars in order to assess proportions of labile and recalcitrant organic matter and to study the evolution of soil organic matter in soils amended with biochar. Thermal analysis could be used to determine the proximate analysis, i.e., the percentage of humidity, volatile matter and fixed carbon or to calculate the thermostability index, previously identified as a reliable parameter for evaluating the level of stability of organic matter in organic wastes and biochar. Relationship between the stability of biochar, the raw material and the pyrolysis conditions could be established by thermal analysis techniques.

  5. Prediction of transposable element derived enhancers using chromatin modification profiles.

    Directory of Open Access Journals (Sweden)

    Ahsan Huda

    Full Text Available Experimentally characterized enhancer regions have previously been shown to display specific patterns of enrichment for several different histone modifications. We modelled these enhancer chromatin profiles in the human genome and used them to guide the search for novel enhancers derived from transposable element (TE sequences. To do this, a computational approach was taken to analyze the genome-wide histone modification landscape characterized by the ENCODE project in two human hematopoietic cell types, GM12878 and K562. We predicted the locations of 2,107 and 1,448 TE-derived enhancers in the GM12878 and K562 cell lines respectively. A vast majority of these putative enhancers are unique to each cell line; only 3.5% of the TE-derived enhancers are shared between the two. We evaluated the functional effect of TE-derived enhancers by associating them with the cell-type specific expression of nearby genes, and found that the number of TE-derived enhancers is strongly positively correlated with the expression of nearby genes in each cell line. Furthermore, genes that are differentially expressed between the two cell lines also possess a divergent number of TE-derived enhancers in their vicinity. As such, genes that are up-regulated in the GM12878 cell line and down-regulated in K562 have significantly more TE-derived enhancers in their vicinity in the GM12878 cell line and vice versa. These data indicate that human TE-derived sequences are likely to be involved in regulating cell-type specific gene expression on a broad scale and suggest that the enhancer activity of TE-derived sequences is mediated by epigenetic regulatory mechanisms.

  6. Does Premarital Cohabitation Predict Subsequent Marital Stability and Marital Quality? A Meta-Analysis

    Science.gov (United States)

    Jose, Anita; O'Leary, K. Daniel; Moyer, Anne

    2010-01-01

    Cohabitation with a romantic partner has become common in recent decades. This meta-analysis examined the link between premarital cohabitation and marital stability (k = 16) and marital quality (k = 12). Cohabitation had a significant negative association with both marital stability and marital quality. The negative predictive effect on marital…

  7. Camp stability predicts patterns of hunter-gatherer cooperation.

    Science.gov (United States)

    Smith, Daniel; Dyble, Mark; Thompson, James; Major, Katie; Page, Abigail E; Chaudhary, Nikhil; Salali, Gul Deniz; Vinicius, Lucio; Migliano, Andrea Bamberg; Mace, Ruth

    2016-07-01

    Humans regularly cooperate with non-kin, which has been theorized to require reciprocity between repeatedly interacting and trusting individuals. However, the role of repeated interactions has not previously been demonstrated in explaining real-world patterns of hunter-gatherer cooperation. Here we explore cooperation among the Agta, a population of Filipino hunter-gatherers, using data from both actual resource transfers and two experimental games across multiple camps. Patterns of cooperation vary greatly between camps and depend on socio-ecological context. Stable camps (with fewer changes in membership over time) were associated with greater reciprocal sharing, indicating that an increased likelihood of future interactions facilitates reciprocity. This is the first study reporting an association between reciprocal cooperation and hunter-gatherer band stability. Under conditions of low camp stability individuals still acquire resources from others, but do so via demand sharing (taking from others), rather than based on reciprocal considerations. Hunter-gatherer cooperation may either be characterized as reciprocity or demand sharing depending on socio-ecological conditions.

  8. Prediction and Stability of Reading Problems in Middle Childhood

    Science.gov (United States)

    Ritchey, Kristen D.; Silverman, Rebecca D.; Schatschneider, Christopher; Speece, Deborah L.

    2015-01-01

    The longitudinal prediction of reading problems from fourth grade to sixth grade was investigated with a sample of 173 students. Reading problems at the end of sixth grade were defined by significantly below average performance (= 15th percentile) on reading factors defining word reading, fluency, and reading comprehension. Sixth grade poor reader…

  9. Study on Integrated Control of Vehicle Yaw and Rollover Stability Using Nonlinear Prediction Model

    Directory of Open Access Journals (Sweden)

    Jianyong Cao

    2013-01-01

    Full Text Available This paper proposes the integrated controller of the yaw and rollover stability controls based on the prediction model. A nonlinear 3-DoF vehicle model with a piecewise linearization tire model is built up as the rollover predictive model, and its accuracy is verified by vehicle tests. A yaw stability controller and a rollover stability controller are proposed, respectively. Then coordinated control strategy is investigated for the integration of vehicle yaw and roll stability controls. The additional yaw torque and braking torque of each wheel are calculated. The unified command of valves is sent combined with ABS control algorithm. Virtual tests in CarSim are carried out, including slalom condition and double-lane change condition. Results indicate that the coordinated control algorithm improves vehicle yaw and roll stability effectively.

  10. High level model predictive control for plug-and-play process control with stability guaranty

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob

    2010-01-01

    In this paper a method for designing a stabilizing high level model predictive controller for a hierarchical plug- and-play process is presented. This is achieved by abstracting the lower layers of the controller structure as low order models with uncertainty and by using a robust model predictive...

  11. Comparison of Linear Prediction Methods in Terms of Sparsity, Stability and Robustness to Reverberation

    NARCIS (Netherlands)

    Koutrouvelis, A.I.; Heusdens, R.; Gaubitch, N.D.

    2014-01-01

    The aim of this paper is to provide an experimental evaluation of five linear prediction methods in terms of sparsity, stability and robustness to reverberation. Moreover, we show that all the considered methods can be derived from a general linear prediction optimization problem. It is empirically

  12. Investigation of the effects of human body stability on joint angles’ prediction

    Energy Technology Data Exchange (ETDEWEB)

    Pasha Zanoosi, A. A., E-mail: aliakbar.pasha@yahoo.com, E-mail: aliakbar.pasha@qiau.ac.ir [Islamic Azad University, Faculty of Industrial & Mechanical Engineering, Qazvin Branch (Iran, Islamic Republic of); Naderi, D.; Sadeghi-Mehr, M.; Feri, M. [Bu Ali-Sina University, Mechanical Engineering Department, Faculty of Engineering (Iran, Islamic Republic of); Beheshtiha, A. Sh. [Leibniz Universität Hannover, Institute of Mechanics and Computational Mechanics (Germany); Fallahnejad, K. [Flinders University, Discipline of Mechanical Engineering, School of Computer Science, Engineering and Mathematics (Australia)

    2015-10-15

    Loosing stability control in elderly or paralyzed has motivated researchers to study how a stability control system works and how to determine its state at every time instant. Studying the stability of a human body is not only an important problem from a scientific viewpoint, but also finally leads to new designs of prostheses and orthoses and rehabilitation methods. Computer modeling enables researchers to study and describe the reactions and propose a suitable and optimized motion pattern to strengthen the neuromuscular system and helps a human body maintain its stability. A perturbation as a tilting is exposed to an underfoot plate of a musculoskeletal model of the body to study the stability. The studied model of a human body included four links and three degrees of freedom with eight muscles in the sagittal plane. Lagrangian dynamics was used for deriving equations of motion and muscles were modeled using Hill’s model. Using experimental data of joint trajectories for a human body under tilting perturbation, forward dynamics has been applied to predict joint trajectories and muscle activation. This study investigated the effects of stability on predicting body joints’ motion. A new stability function for a human body, based on the zero moment point, has been employed in a forward dynamics procedure using a direct collocation method. A multi-objective optimization based on genetic algorithm has been proposed to employ stability as a robotic objective function along with muscle stresses as a biological objective function. The obtained results for joints’ motion were compared to experimental data. The results show that, for this type of perturbations, muscle stresses are in conflict with body stability. This means that more body stability requires more stresses in muscles and reverse. Results also show the effects of the stability objective function in better prediction of joint trajectories.

  13. Dynamical Stability and Predictability of Football Players: The Study of One Match

    Directory of Open Access Journals (Sweden)

    Micael S. Couceiro

    2014-01-01

    Full Text Available The game of football demands new computational approaches to measure individual and collective performance. Understanding the phenomena involved in the game may foster the identification of strengths and weaknesses, not only of each player, but also of the whole team. The development of assertive quantitative methodologies constitutes a key element in sports training. In football, the predictability and stability inherent in the motion of a given player may be seen as one of the most important concepts to fully characterise the variability of the whole team. This paper characterises the predictability and stability levels of players during an official football match. A Fractional Calculus (FC approach to define a player’s trajectory. By applying FC, one can benefit from newly considered modeling perspectives, such as the fractional coefficient, to estimate a player’s predictability and stability. This paper also formulates the concept of attraction domain, related to the tactical region of each player, inspired by stability theory principles. To compare the variability inherent in the player’s process variables (e.g., distance covered and to assess his predictability and stability, entropy measures are considered. Experimental results suggest that the most predictable player is the goalkeeper while, conversely, the most unpredictable players are the midfielders. We also conclude that, despite his predictability, the goalkeeper is the most unstable player, while lateral defenders are the most stable during the match.

  14. Three-level prediction of protein function by combining profile-sequence search, profile-profile search, and domain co-occurrence networks.

    Science.gov (United States)

    Wang, Zheng; Cao, Renzhi; Cheng, Jianlin

    2013-01-01

    Predicting protein function from sequence is useful for biochemical experiment design, mutagenesis analysis, protein engineering, protein design, biological pathway analysis, drug design, disease diagnosis, and genome annotation as a vast number of protein sequences with unknown function are routinely being generated by DNA, RNA and protein sequencing in the genomic era. However, despite significant progresses in the last several years, the accuracy of protein function prediction still needs to be improved in order to be used effectively in practice, particularly when little or no homology exists between a target protein and proteins with annotated function. Here, we developed a method that integrated profile-sequence alignment, profile-profile alignment, and Domain Co-Occurrence Networks (DCN) to predict protein function at different levels of complexity, ranging from obvious homology, to remote homology, to no homology. We tested the method blindingly in the 2011 Critical Assessment of Function Annotation (CAFA). Our experiments demonstrated that our three-level prediction method effectively increased the recall of function prediction while maintaining a reasonable precision. Particularly, our method can predict function terms defined by the Gene Ontology more accurately than three standard baseline methods in most situations, handle multi-domain proteins naturally, and make ab initio function prediction when no homology exists. These results show that our approach can combine complementary strengths of most widely used BLAST-based function prediction methods, rarely used in function prediction but more sensitive profile-profile comparison-based homology detection methods, and non-homology-based domain co-occurrence networks, to effectively extend the power of function prediction from high homology, to low homology, to no homology (ab initio cases).

  15. Predicting 3D Structure, Flexibility, and Stability of RNA Hairpins in Monovalent and Divalent Ion Solutions

    Science.gov (United States)

    Shi, Ya-Zhou; Jin, Lei; Wang, Feng-Hua; Zhu, Xiao-Long; Tan, Zhi-Jie

    2015-01-01

    A full understanding of RNA-mediated biology would require the knowledge of three-dimensional (3D) structures, structural flexibility, and stability of RNAs. To predict RNA 3D structures and stability, we have previously proposed a three-bead coarse-grained predictive model with implicit salt/solvent potentials. In this study, we further develop the model by improving the implicit-salt electrostatic potential and including a sequence-dependent coaxial stacking potential to enable the model to simulate RNA 3D structure folding in divalent/monovalent ion solutions. The model presented here can predict 3D structures of RNA hairpins with bulges/internal loops (RNA hairpins with bulge loops of different lengths at several divalent/monovalent ion conditions. In addition, the model successfully predicts the stability of RNA hairpins with various loops/stems in divalent/monovalent ion solutions. PMID:26682822

  16. Probabilistic stability and "tall" wind profiles: theory and method for use in wind resource assessment

    DEFF Research Database (Denmark)

    Kelly, Mark C.; Troen, Ib

    2016-01-01

    A model has been derived for calculating the aggregate effects of stability and the finite height of the planetary boundary layer upon the long-term mean wind profile. A practical implementation of this probabilistic extended similarity-theory model is made, including its incorporation within...... to the methodology. Results of the modeling are shown for a number of sites, with discussion of the models’ efficacy and the relative improvement shown by the new model, for situations where a user lacks local heat flux information, as well as performance of the new model using measured flux statistics. Further...

  17. Predicting the Thermal Stability of Nitroaromatic Compounds Using Chemoinformatic Tools.

    Science.gov (United States)

    Fayet, Guillaume; Del Rio, Alberto; Rotureau, Patricia; Joubert, Laurent; Adamo, Carlo

    2011-06-01

    In the framework of the European REACH regulation major attention was recently devoted to toxicological and ecotoxicological problems while little attention has been dedicated to other important applications concerning chemical hazards, for instance, explosive properties. In this work different chemoinformatic tools such as partial least squares, multilinear regressions, and decision trees have been used for the development of a novel quantitative structure-property relationships to predict the heat of decomposition of a series of nitroaromatic compounds. Models were conceived in order to follow the regulatory requirements according to OECD principles for the validation of QSAR methods. Three models derived with MLR, PLS and decision tree techniques were developed, validated (internally and externally) and their applicability domains have been defined and analyzed. All models proved to be reliable with remarkable robustness in terms of full cross-validation scheme and showed good predictive power toward the external validation set. These models also present a large applicability domain within nitrobenzene derivatives and are easy to implement and interpret in terms of subjacent mechanisms. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Psoriasis prediction from genome-wide SNP profiles

    Directory of Open Access Journals (Sweden)

    Fang Xiangzhong

    2011-01-01

    Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.

  19. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot.

    Science.gov (United States)

    Carnaval, Ana Carolina; Hickerson, Michael J; Haddad, Célio F B; Rodrigues, Miguel T; Moritz, Craig

    2009-02-06

    Biodiversity hotspots, representing regions with high species endemism and conservation threat, have been mapped globally. Yet, biodiversity distribution data from within hotspots are too sparse for effective conservation in the face of rapid environmental change. Using frogs as indicators, ecological niche models under paleoclimates, and simultaneous Bayesian analyses of multispecies molecular data, we compare alternative hypotheses of assemblage-scale response to late Quaternary climate change. This reveals a hotspot within the Brazilian Atlantic forest hotspot. We show that the southern Atlantic forest was climatically unstable relative to the central region, which served as a large climatic refugium for neotropical species in the late Pleistocene. This sets new priorities for conservation in Brazil and establishes a validated approach to biodiversity prediction in other understudied, species-rich regions.

  20. Trajectory Tracking and Stabilization of a Quadrotor Using Model Predictive Control of Laguerre Functions

    Directory of Open Access Journals (Sweden)

    Mapopa Chipofya

    2015-01-01

    Full Text Available This paper presents a solution to stability and trajectory tracking of a quadrotor system using a model predictive controller designed using a type of orthonormal functions called Laguerre functions. A linear model of the quadrotor is derived and used. To check the performance of the controller we compare it with a linear quadratic regulator and a more traditional linear state space MPC. Simulations for trajectory tracking and stability are performed in MATLAB and results provided in this paper.

  1. Drought Prediction for Socio-Cultural Stability Project

    Science.gov (United States)

    Peters-Lidard, Christa; Eylander, John B.; Koster, Randall; Narapusetty, Balachandrudu; Kumar, Sujay; Rodell, Matt; Bolten, John; Mocko, David; Walker, Gregory; Arsenault, Kristi; hide

    2014-01-01

    The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture

  2. Development, stability and in vitro delivery profile of new loratadine-loaded nanoparticles

    Directory of Open Access Journals (Sweden)

    Jesus Rafael Rodriguez Amado

    2017-12-01

    Full Text Available Purpose: Loratadine is used as antihistaminic without side effects in nervous systems. This drug is a weak base and it is absorbed from the intestine. The nitrogen of the pyridine ring is protonated in the stomach affecting the oral bioavailability. The aim of this paper was obtaining, characterize and evaluate the release profiles and the stability of a gastroresistant loratadine nanosuspension. Methods: The nanosuspension was prepared by the solvent displacement evaporation method, using three different polymers (Eudragit® L 100 55, Kollicoat® MAE 100P and PEG 4000 and Polysorbate 80. Dynamic Light Scattering was used for evaluating the particle size (PS, zeta potential, and conductivity of the nanosuspension. Loratadine release profiles were evaluated in simulated gastrointestinal fluids. The shelf and accelerated stability were assessed during three months. Results: Nanosuspension particle size was 45.94 ± 0.50 nm, with a low polydispersion index (PdI, 0.300. Kollicoat® MAE 100P produced a hard and flexible coating layer. In simulated intestinal fluids, the 100 percent of loratadine was released in 40 min, while in simulated stomach fluids the release was lesser than 5%. Nanosuspension presented a good physicochemical stability showing a reduction in PS and PdI after three months (43.29 ± 0.16 and 0.250; respectively. Conclusions: A promissory loratadine nanosuspension for loratadine intestinal delivery was obtained, by using a low energy method, which is an advantage for a possible scale up for practical purpose.

  3. Stability-based comparison of class discovery methods for DNA copy number profiles.

    Directory of Open Access Journals (Sweden)

    Isabel Brito

    Full Text Available MOTIVATION: Array-CGH can be used to determine DNA copy number, imbalances in which are a fundamental factor in the genesis and progression of tumors. The discovery of classes with similar patterns of array-CGH profiles therefore adds to our understanding of cancer and the treatment of patients. Various input data representations for array-CGH, dissimilarity measures between tumor samples and clustering algorithms may be used for this purpose. The choice between procedures is often difficult. An evaluation procedure is therefore required to select the best class discovery method (combination of one input data representation, one dissimilarity measure and one clustering algorithm for array-CGH. Robustness of the resulting classes is a common requirement, but no stability-based comparison of class discovery methods for array-CGH profiles has ever been reported. RESULTS: We applied several class discovery methods and evaluated the stability of their solutions, with a modified version of Bertoni's [Formula: see text]-based test [1]. Our version relaxes the assumption of independency required by original Bertoni's [Formula: see text]-based test. We conclude that Minimal Regions of alteration (a concept introduced by [2] for input data representation, sim [3] or agree [4] for dissimilarity measure and the use of average group distance in the clustering algorithm produce the most robust classes of array-CGH profiles. AVAILABILITY: The software is available from http://bioinfo.curie.fr/projects/cgh-clustering. It has also been partly integrated into "Visualization and analysis of array-CGH"(VAMP[5]. The data sets used are publicly available from ACTuDB [6].

  4. Topology-Based Approach to Predict Relative Stabilities of Charged and Functionalized Fullerenes.

    Science.gov (United States)

    Wang, Yang; Díaz-Tendero, Sergio; Alcami, Manuel; Martin, Fernando

    2018-01-27

    Understanding the relationship between structure and stability is one of the fundamental aspects of fullerene chemistry, as the number of possible cage isomers is very large and complexity increases by orders of magnitude when chemical groups are attached to the fullerene cage. The well-established stability rules valid for neutral fullerenes do not apply to many charged or functionalized fullerenes. Here we present the theory, implementation and applications of two simple topology-based models that allow one to predict the relative stability of charged and functionalized fullerenes without the need for quantum chemistry calculations: (i) the charge stabilization index (CSI) model, based on the concepts of cage connectivity and frontier π orbitals, which offers a general framework for the relative stability of both positively and negatively charged fullerenes, as well as endohedral metallofullerenes, and (ii) the exohedral fullerene stabilization index (XSI) model, which incorporates all key factors governing the stability of exohedral fullerenes, namely, π delocalization, σ strain and steric hindrance between addends. Based exclusively on topological information, both models are powerful prescreening tools for predicting the most stable structures of a large number of charged and functionalized fullerenes. For easy use by fullerene chemists, both models have been implemented in the FullFun (for Fullerene Functionalization) software package, whose effectiveness and efficiency are demonstrated by some illustrative examples.

  5. Hair care formulations containing argan oil: development, stability and texture profile

    Directory of Open Access Journals (Sweden)

    Stefânia Duz Delsin

    2015-12-01

    Full Text Available The aim of this study was to develop hair care cosmetic formulations containing argan oil to evaluate the stability and texture profile of these formulations. Shampoos, conditioners and leave-in formulations were developed with or without (vehicle argan oil in concentrations of 0.1, 2.0 and 2.0% (w/w respectively. The formulations were stored at room temperature (25°C, 37°C and 45°C for a period of 28 days and submitted to spreadability and texture tests using the Texture Analyser. For this purpose, work of shear and consistency parameters were determined. The results have shown that all formulations were stable and the argan oil-based formulations had a better spreadability when compared with the vehicle. This is a desirable effect, once cosmetic formulations which presents a lower values of work of shear are better accepted by cosmetic sensory panels. In addition, no difference was found between conditioners with or without argan oil in terms of texture profile, and leave-informulation with argan oil showed an increased consistency when compared with the vehicle. Finally, formulations with argan oil showed better the texture profile, therefore, it is a potential ingredient for use in hair care formulations.

  6. Compact Web browsing profiles for click-through rate prediction

    DEFF Research Database (Denmark)

    Fruergaard, Bjarne Ørum; Hansen, Lars Kai

    2014-01-01

    In real time advertising we are interested in finding features that improve click-through rate prediction. One source of available information is the bipartite graph of websites previously engaged by identifiable users. In this work, we investigate three different decompositions of such a graph...

  7. NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure.

    Science.gov (United States)

    Turner, Douglas H; Mathews, David H

    2010-01-01

    The Nearest Neighbor Database (NNDB, http://rna.urmc.rochester.edu/NNDB) is a web-based resource for disseminating parameter sets for predicting nucleic acid secondary structure stabilities. For each set of parameters, the database includes the set of rules with descriptive text, sequence-dependent parameters in plain text and html, literature references to experiments and usage tutorials. The initial release covers parameters for predicting RNA folding free energy and enthalpy changes.

  8. NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure

    OpenAIRE

    Turner, Douglas H.; David H Mathews

    2009-01-01

    The Nearest Neighbor Database (NNDB, http://rna.urmc.rochester.edu/NNDB) is a web-based resource for disseminating parameter sets for predicting nucleic acid secondary structure stabilities. For each set of parameters, the database includes the set of rules with descriptive text, sequence-dependent parameters in plain text and html, literature references to experiments and usage tutorials. The initial release covers parameters for predicting RNA folding free energy and enthalpy changes.

  9. Geometrical theory to predict eccentric photorefraction intensity profiles in the human eye

    Science.gov (United States)

    Roorda, Austin; Campbell, Melanie C. W.; Bobier, W. R.

    1995-08-01

    In eccentric photorefraction, light returning from the retina of the eye is photographed by a camera focused on the eye's pupil. We use a geometrical model of eccentric photorefraction to generate intensity profiles across the pupil image. The intensity profiles for three different monochromatic aberration functions induced in a single eye are predicted and show good agreement with the measured eccentric photorefraction intensity profiles. A directional reflection from the retina is incorporated into the calculation. Intensity profiles for symmetric and asymmetric aberrations are generated and measured. The latter profile shows a dependency on the source position and the meridian. The magnitude of the effect of thresholding on measured pattern extents is predicted. Monochromatic aberrations in human eyes will cause deviations in the eccentric photorefraction measurements from traditional crescents caused by defocus and may cause misdiagnoses of ametropia or anisometropia. Our results suggest that measuring refraction along the vertical meridian is preferred for screening studies with the eccentric photorefractor.

  10. Effects of DTM resolution on slope steepness and soil loss prediction on hillslope profiles

    Science.gov (United States)

    Eder Paulo Moreira; William J. Elliot; Andrew T. Hudak

    2011-01-01

    Topographic attributes play a critical role in predicting erosion in models such as the Water Erosion Prediction Project (WEPP). The effects of four different high resolution hillslope profiles were studied using four different DTM resolutions: 1-m, 3-m, 5-m and 10-m. The WEPP model used a common scenario encountered in the forest environment and the selected hillslope...

  11. Revisiting internal gravity waves analysis using GPS RO density profiles: comparison with temperature profiles and application for wave field stability study

    Directory of Open Access Journals (Sweden)

    P. Pisoft

    2018-01-01

    Full Text Available We revise selected findings regarding the utilization of Global Positioning System radio occultation (GPS RO density profiles for the analysis of internal gravity waves (IGW, introduced by Sacha et al. (2014. Using various GPS RO datasets, we show that the differences in the IGW spectra between the dry-temperature and dry-density profiles that were described in the previous study as a general issue are in fact present in one specific data version only. The differences between perturbations in the temperature and density GPS RO profiles do not have any physical origin, and there is not the information loss of IGW activity that was suggested in Sacha et al. (2014. We investigate the previously discussed question of the temperature perturbations character when utilizing GPS RO dry-temperature profiles, derived by integration of the hydrostatic balance. Using radiosonde profiles as a proxy for GPS RO, we provide strong evidence that the differences in IGW perturbations between the real and retrieved temperature profiles (which are based on the assumption of hydrostatic balance include a significant nonhydrostatic component that is present sporadically and might be either positive or negative. The detected differences in related spectra of IGW temperature perturbations are found to be mostly about ±10 %. The paper also presents a detailed study on the utilization of GPS RO density profiles for the characterization of the wave field stability. We have analyzed selected stability parameters derived from the density profiles together with a study of the vertical rotation of the wind direction. Regarding the Northern Hemisphere the results point to the western border of the Aleutian high, where potential IGW breaking is detected. These findings are also supported by an analysis of temperature and wind velocity profiles. Our results confirm advantages of the utilization of the density profiles for IGW analysis.

  12. Stability of a neural predictive controller scheme on a neural model

    DEFF Research Database (Denmark)

    Luther, Jim Benjamin; Sørensen, Paul Haase

    2009-01-01

    In previous works presenting various forms of neural-network-based predictive controllers, the main emphasis has been on the implementation aspects, i.e. the development of a robust optimization algorithm for the controller, which will be able to perform in real time. However, the stability issue....... The resulting controller is tested on a nonlinear pneumatic servo system....

  13. Norovirus-like VP1 particles exhibit isolate dependent stability profiles

    Science.gov (United States)

    Pogan, Ronja; Schneider, Carola; Reimer, Rudolph; Hansman, Grant; Uetrecht, Charlotte

    2018-02-01

    Noroviruses are the main cause of viral gastroenteritis with new variants emerging frequently. There are three norovirus genogroups infecting humans. These genogroups are divided based on the sequence of their major capsid protein, which is able to form virus-like particles (VLPs) when expressed recombinantly. VLPs of the prototypical GI.1 Norwalk virus are known to disassemble into specific capsid protein oligomers upon alkaline treatment. Here, native mass spectrometry and electron microscopy on variants of GI.1 and of GII.17 were performed, revealing differences in terms of stability between these groups. Beyond that, these experiments indicate differences even between variants within a genotype. The capsid stability was monitored in different ammonium acetate solutions varying both in ionic strength and pH. The investigated GI.1 West Chester isolate showed comparable disassembly profiles to the previously studied GI.1 Norwalk virus isolate. However, differences were observed with the West Chester being more sensitive to alkaline pH. In stark contrast to that, capsids of the variant belonging to the currently prevalent genogroup GII were stable in all tested conditions. Both variants formed smaller capsid particles already at neutral pH. Certain amino acid substitutions in the S domain of West Chester relative to the Norwalk virus potentially result in the formation of these T  =  1 capsids.

  14. Nutritional Profile and Chemical Stability of Pasta Fortified with Tilapia (Oreochromis niloticus) Flour.

    Science.gov (United States)

    Monteiro, Maria Lúcia G; Mársico, Eliane T; Soares, Manoel S; Magalhães, Amanda O; Canto, Anna Carolina V C S; Costa-Lima, Bruno R C; Alvares, Thiago S; Conte, Carlos A

    2016-01-01

    Physicochemical parameters of pasta enriched with tilapia (Oreochromis niloticus) flour were investigated. Five formulations were prepared with different concentrations of tilapia flour as partial substitute of wheat flour: pasta without tilapia flour (PTF0%), pasta with 6% (PTF6%), 12% (PTF12%), 17% (PTF17%), and 23% (PTF23%) of tilapia flour. The formulations were assessed for proximate composition, fatty acid and amino acid profile on day 1 whereas, instrumental color parameters (L*, a* and b* values), pH, water activity (aw), and lipid and protein oxidation were evaluated on days 1, 7, 14, and 21 of storage at 25°C. Fortification with tilapia flour increased (p water activity while redness, yellowness, pH values, and lipid oxidation were increased (p stability at 25°C. In general, protein oxidation was greater (p food industry for the nutritional enrichment of traditional pasta with negligible negative effects on the chemical stability of the final product during 21 days at 25°C.

  15. Numerical Prediction of the Influence of Thrust Reverser on Aeroengine's Aerodynamic Stability

    Science.gov (United States)

    Zhiqiang, Wang; Xigang, Shen; Jun, Hu; Xiang, Gao; Liping, Liu

    2017-11-01

    A numerical method was developed to predict the aerodynamic stability of a high bypass ratio turbofan engine, at the landing stage of a large transport aircraft, when the thrust reverser was deployed. 3D CFD simulation and 2D aeroengine aerodynamic stability analysis code were performed in this work, the former is to achieve distortion coefficient for the analysis of engine stability. The 3D CFD simulation was divided into two steps, the single engine calculation and the integrated aircraft and engine calculation. Results of the CFD simulation show that with the decreasing of relative wind Mach number, the engine inlet will suffer more severe flow distortion. The total pressure and total temperature distortion coefficients at the inlet of the engines were obtained from the results of the numerical simulation. Then an aeroengine aerodynamic stability analysis program was used to quantitatively analyze the aerodynamic stability of the high bypass ratio turbofan engine. The results of the stability analysis show that the engine can work stably, when the reverser flow is re-ingested. But the anti-distortion ability of the booster is weaker than that of the fan and high pressure compressor. It is a weak link of engine stability.

  16. Stability and relative validity of the Neuromuscular Disease Impact Profile (NMDIP).

    Science.gov (United States)

    Bos, Isaäc; Kuks, Jan B M; Almansa, Josué; Kremer, Hubertus P H; Wynia, Klaske

    2017-05-11

    The aim of this study was to examine the stability and relative validity (RV) of the Neuromuscular Disease Impact Profile (NMDIP) using criterion-related groups. In a previous study the NMDIP-scales showed good internal consistency, convergent and discriminant validity. Known-groups analysis showed that the NMDIP discriminates between categories of extent of limitations. A cross-sectional postal survey study was performed on patients diagnosed with a NMD and registered at the Department of Neurology, University Medical Center Groningen, the Netherlands. Participants were asked to complete the preliminary NMDIP, the Medical Outcome study Short Form Questionnaire (SF-36), the World Health Organization Quality Of Life-abbreviation version (WHOQOL-bref), and two generic domain specific measures: the Groningen Activity Restriction Scale (GARS) and the Impact on Participation and Autonomy Questionnaire (IPAQ). The variables 'Extent of Limitations' and 'Quality of Life' were used to create criterion-related groups. Stability over time was tested using the Wilcoxon Signed Rank Test for paired samples and the intraclass correlation coefficients for repeated measures. RV was examined by comparing the ability of NMDIP with generic multidimensional health impact measures, and domain specific measures in discriminating between criterion-related subgroups using the Kruskal-Wallis H-test. Response rate was 70% (n = 702). The NMDIP-scales showed sufficient stability over time, and satisfactory or strong RV. In general, the NMDIP scales performed as well as or better than the concurrent measurement instruments. The NMDIP proved to be a valid and reliable disease-targeted measure with a broad scope on physical, psychological and social functioning.

  17. REAL-TIME STABILITY AND PROFILE COMPARISON MEASUREMENTS BETWEEN TWO DIFFERENT LTPS.

    Energy Technology Data Exchange (ETDEWEB)

    QIAN, S.; WANG, D.J.

    2005-07-31

    The Long Trace Profiler (LTP) is a precise angle measurement instrument, with a sensitivity and accuracy that can be in the sub-micron radian range. LTP characteristics depend on the particular LTP system schematic design, and the quality of components and assembly. The conditions of temperature, alignment, and mirror support during the measurement process vary between different laboratories, which influences significantly the test repeatability and accuracy. In this paper we introduce a direct comparison method to test the same object at the same point in the same environment at the same time by using two LTPs, which significantly increases the reliability of the comparison. A compact, portable LTP (PTLTP), which can be carried to different laboratories around the world, is used for comparison testing. Stability Comparison experiments between the LTP II at the National Synchrotron Radiation Research Center (NSRRC), and the PTLTP of Brookhaven National Laboratory (BNL) reveal significant differences in performance between the instruments. The experiment is set up so that each optical head simultaneously records both its own sample probe beam and also the probe beam from the other optical head. The two probe beams are reflected from same point on the mirror. Tests show that the stability of the PTLTP with a monolithic beam splitter is 10 times better than the stability of the LTP II which has a separated beam splitter unit. A scheme for comparing scanning measurements of a mirror is introduced. Experimental results show a significant difference between the two LTPs due mainly to distortions in the optical components inside the optical head. A new scheme is proposed for further mirror comparison scanning tests.

  18. Study of the Lactobacillus rhamnosus Lcr35® properties after compression and proposition of a model to predict tablet stability.

    Science.gov (United States)

    Muller, Claudia; Mazel, Vincent; Dausset, Caroline; Busignies, Virginie; Bornes, Stéphanie; Nivoliez, Adrien; Tchoreloff, Pierre

    2014-11-01

    The beneficial effects of probiotic bacteria on human health are now widely acknowledged, and this has prompted growing interest in research and development in the pharmaceutical field. However, to be viable when they reach their target, the bacteria must be able to survive during the manufacturing process and the biological pathway. Tablet form best meets the requirements for protecting acid labile drugs, but the tableting process could be an additional stress for the bacteria. This study evaluated the initial effect of compression pressure on the Lcr35® strain in a vaginal (Lcr regenerans®) and an intestinal (Lcr restituo®) formulation. A stability study was also performed on the tablets and revealed a beneficial effect of this form. The obtained destruction rates (k) demonstrated that the bacterial stability was greater in tablets than in powders (kpowders>ktablets). A new mathematical model was developed combining compression and temperature parameters to predict the bacterial viability at any pressure and time. Moreover, the genetic profile of Lcr35® (Rep-PCR, microarrays), its resistance to acidity and its ability to inhibit Candidaalbicans growth, after compression, were determined to evaluate the target product profile (TPP) in a Quality by Design (QbD) approach. The Rep-PCR analysis validated the strain identity and the microarrays demonstrated the genetic stability of Lcr35® strain after compaction. Additionally, ability to inhibit the C. albicans growth was maintained and the resistance to gastric conditions of Lcr35® was even improved by tableting. As a dosage form, tablets containing probiotic can guarantee that an adequate amount of bacteria reaches the therapeutic target (intestinal or vaginal) and that the product remains stable until the time of consumption. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. StaRProtein, A Web Server for Prediction of the Stability of Repeat Proteins

    Science.gov (United States)

    Xu, Yongtao; Zhou, Xu; Huang, Meilan

    2015-01-01

    Repeat proteins have become increasingly important due to their capability to bind to almost any proteins and the potential as alternative therapy to monoclonal antibodies. In the past decade repeat proteins have been designed to mediate specific protein-protein interactions. The tetratricopeptide and ankyrin repeat proteins are two classes of helical repeat proteins that form different binding pockets to accommodate various partners. It is important to understand the factors that define folding and stability of repeat proteins in order to prioritize the most stable designed repeat proteins to further explore their potential binding affinities. Here we developed distance-dependant statistical potentials using two classes of alpha-helical repeat proteins, tetratricopeptide and ankyrin repeat proteins respectively, and evaluated their efficiency in predicting the stability of repeat proteins. We demonstrated that the repeat-specific statistical potentials based on these two classes of repeat proteins showed paramount accuracy compared with non-specific statistical potentials in: 1) discriminate correct vs. incorrect models 2) rank the stability of designed repeat proteins. In particular, the statistical scores correlate closely with the equilibrium unfolding free energies of repeat proteins and therefore would serve as a novel tool in quickly prioritizing the designed repeat proteins with high stability. StaRProtein web server was developed for predicting the stability of repeat proteins. PMID:25807112

  20. How accurate is Density Functional Theory in Predicting Reaction Energies Relevant to Phase Stability?

    Science.gov (United States)

    Hautier, Geoffroy; Ong, Shyue Ping; Jain, Anubhav; Moore, Charles J.; Ceder, Gerbrand

    2012-02-01

    Density Functional Theory (DFT) computations can be used to build computational phase diagrams that are used to understand the stability of known phases but also to assess the stability of novel, predicted compounds. The quality and predictive power of those phase diagrams rely on the accuracy of DFT in modeling reaction energies and we will present in this talk the results of a large scale comparison between experimentally measured and DFT computed reaction energies. For starters, we will show that only certain reaction energies are directly relevant to phase stability of multicomponent systems and that very often those reaction energies are not the commonly studied reactions from the elements. Using data from different experimental thermochemical tables and DFT high-throughput computing, we will present the results of a statistical study based on more than 130 reaction energies relevant to phase stability and from binary oxides to ternary oxides. We will show that the typical error are around 30 meV/at and therefore an order of magnitude lower than the errors in reaction energies from the elements. Finally, we will discuss the broad implications of our results on the evaluation of ab initio phase diagrams and on the computational prediction of new solid phases.

  1. Cytokine profiles at birth predict malaria severity during infancy.

    Directory of Open Access Journals (Sweden)

    Edward Kabyemela

    Full Text Available BACKGROUND: Severe malaria risk varies between individuals, and most of this variation remains unexplained. Here, we examined the hypothesis that cytokine profiles at birth reflect inter-individual differences that persist and influence malaria parasite density and disease severity throughout early childhood. METHODS AND FINDINGS: Cytokine levels (TNF-α, IFN-γ, IL-1β, IL-4, IL-5, IL-6 and IL-10 were measured at birth (cord blood; N=783 and during subsequent routine follow-up visits (peripheral blood for children enrolled between 2002 and 2006 into a birth cohort in Muheza, Tanzania. Children underwent blood smear and clinical assessments every 2-4 weeks, and at the time of any illness. Cord blood levels of all cytokines were positively correlated with each other (Spearman's rank correlation. Cord levels of IL-1β and TNF-α (but not other cytokines correlated with levels of the same cytokine measured at routine visits during early life (P < 0.05. Higher cord levels of IL-1β but not TNF-α were associated with lower parasite densities during infancy (P=0.003; Generalized Estimating Equation (GEE method, with an average ~40% reduction versus children with low cord IL-1β levels, and with decreased risk of severe malaria during follow-up (Cox regression: adjusted hazard ratio (95% CI 0.60 (0.39-0.92, P = 0.02. CONCLUSION: IL-1β levels at birth are related to future IL-1β levels as well as the risk of severe malaria in early life. The effect on severe malaria risk may be due in part to the effect of inflammatory cytokines to control parasite density.

  2. A Model for the Prediction of Tobacco Temperature and Oxygen Profiles in Warehouse Aging Process

    Directory of Open Access Journals (Sweden)

    Zheng Y

    2014-12-01

    Full Text Available A mathematical model on the temperature and oxygen profiles for the tobacco warehouse aging process was formulated and solved by numeric analysis. The model parameters were obtained using the non-linear regression method by fitting several years measured temperatures to the model. The R square value between measured and calculated tobacco temperatures in warehouse aging process are all over 0.95. The proposed model can be used to predict the tobacco hogshead temperature profile at different time and positions with ambient temperature, tobacco moisture contents and pH. At the same time, the model also predicts the oxygen profile in the hogshead. The effects of the ambient temperature, pH, void fraction, the reaction active energy, oxygen diffusivity, and the oxygen consumption rate constant on the temperature profile were studied.

  3. Hidden Markov model to predict the amino acid profile

    Science.gov (United States)

    Handamari, Endang Wahyu

    2017-12-01

    Sequence alignment is the basic method in sequence analysis, which is the process of composing or aligning two or more primary sequences so that the sequence similarity is apparent. One of the uses of this method is to predict the structure or function of an unknown protein by using a known protein information structure or function if the protein has the same sequence in database. Protein are macromolecules that make up more than half of the cell. Proteins are a chain of 20 amino acid combinations. Each type of protein has a unique number and sequence of amino acids. The method that can be applied for sequence alignment is the Genetic Algorithm, the other method is related to the Hidden Markov Model (HMM). The Hidden Markov Model (HMM) is a developmental form of the Markov Chain, which can be applied in cases that can not be directly observed. As Observed State (O) for sequence alignment is the sequence of amino acids in three categories: deletion, insertion and match. As for the Hidden State is the amino acid residue, which can determine the family protein corresponds to observation O.

  4. Benchmarking and qualification of the NUFREQ-NPW code for best estimate prediction of multichannel core stability margins

    Energy Technology Data Exchange (ETDEWEB)

    Taleyarkhan, R.P. (Westinghouse Commercial, Nuclear Fuel Division, Pittsburgh, PA 15230 (United States)); McFarlane, A.F. (Westinghouse Commercial, Nuclear Fuel Division, Pittsburgh, PA 15230 (United States)); Lahey, R.T. Jr. (Department of Nuclear, Engineering and Engineering Physics, Rensselaer Polytechnic Institute, Troy, NY 12181 (United States)); Podowski, M.Z. (Department of Nuclear, Engineering and Engineering Physics, Rensselaer Polytechnic Institute, Troy, NY 12181 (United States))

    1994-11-15

    The NUFREQ-NP (G.C. Park et al. NUREG/CR-3375, 1983; S.J. Peng et al. NUREG/CR-4116, 1984; S.J. Peng et al. Nucl. Sci. Eng. 88 (1988) 404-411) code was modified and set up at Westinghouse, USA, for mixed fuel type multichannel core-wide stability analysis. The resulting code, NUFREQ-NPW, allows for variable axial power profiles between channel groups and can handle mixed fuel types.Various models incorporated into NUFREQ-NPW were systematically compared against the Westinghouse channel stability analysis code MAZDA-NF (R. Taleyarkhan et al. J. Heat Transfer 107 (February 1985) 175-181; NUREG/CR2972, 1983), for which the mathematical model was developed in an entirely different manner. Excellent agreement was obtained which verified the thermal-hydraulic modeling and coding aspects. Detailed comparisons were also performed against nuclear-coupled reactor core stability data. All 13 Peach Bottom-2 EOC-2/3 low flow stability tests (L.A. Carmichael and R.O. Neimi, EPRI NP-564, Project 1020-1, 1978; F.B. Woffinden and R.O. Neimi, EPRI, NP 0972, Project 1020-2, 1981) were simulated. A key aspect for code qualification involved the development of a physically based empirical algorithm to correct for the effect of core inlet flow development on subcooled boiling. Various other modeling assumptions were tested and sensitivity studies performed. Good agreement was obtained between NUFREQ-NPW predictions and data. ((orig.))

  5. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    Science.gov (United States)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2015-10-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

  6. Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2015-01-01

    Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

  7. Clinical, nociceptive and psychological profiling to predict acute pain after total knee arthroplasty

    DEFF Research Database (Denmark)

    Luna, I E; Kehlet, H; Petersen, M A

    2017-01-01

    outcome. Predictive variables collected prior to surgery included demographics, nociceptive testing (pressure pain threshold (PPT), cold pressor tolerance, electrical pain threshold and tolerance) and psychological profile (pain catastrophizing scale (PCS) and hospital anxiety and depression scale...... catastrophizing are predictive of moderate severe post-TKA pain. If validated in a larger population, the clinically applicable tests should be considered in future interventions aiming to minimize post-operative pain in high-risk patients....

  8. Comparison of gene sets for expression profiling: prediction of metastasis from low-malignant breast cancer

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

    2007-01-01

    -six tumors from low-risk patients and 34 low-malignant T2 tumors from patients with slightly higher risk have been examined by genome-wide gene expression analysis. Nine prognostic gene sets were tested in this data set. RESULTS: A 32-gene profile (HUMAC32) that accurately predicts metastasis has previously...... sets, mainly developed in high-risk cancers, predict metastasis from low-malignant cancer....

  9. Membrane Protein Stability Analyses by Means of Protein Energy Profiles in Case of Nephrogenic Diabetes Insipidus

    Directory of Open Access Journals (Sweden)

    Florian Heinke

    2012-01-01

    Full Text Available Diabetes insipidus (DI is a rare endocrine, inheritable disorder with low incidences in an estimated one per 25,000–30,000 live births. This disease is characterized by polyuria and compensatory polydypsia. The diverse underlying causes of DI can be central defects, in which no functional arginine vasopressin (AVP is released from the pituitary or can be a result of defects in the kidney (nephrogenic DI, NDI. NDI is a disorder in which patients are unable to concentrate their urine despite the presence of AVP. This antidiuretic hormone regulates the process of water reabsorption from the prourine that is formed in the kidney. It binds to its type-2 receptor (V2R in the kidney induces a cAMP-driven cascade, which leads to the insertion of aquaporin-2 water channels into the apical membrane. Mutations in the genes of V2R and aquaporin-2 often lead to NDI. We investigated a structure model of V2R in its bound and unbound state regarding protein stability using a novel protein energy profile approach. Furthermore, these techniques were applied to the wild-type and selected mutations of aquaporin-2. We show that our results correspond well to experimental water ux analysis, which confirms the applicability of our theoretical approach to equivalent problems.

  10. Quality Characteristics, Nutraceutical Profile, and Storage Stability of Aloe Gel-Papaya Functional Beverage Blend

    Directory of Open Access Journals (Sweden)

    Pushkala Ramachandran

    2014-01-01

    Full Text Available Aloe vera gel, well known for its nutraceutical potential, is being explored as a functional ingredient in a wide array of health foods and drinks. Processing of exotic fruits and herbal botanicals into functional beverage is an emerging sector in food industry. The present study was undertaken to develop a spiced functional RTS beverage blend using Aloe gel (AG and papaya. Aloe gel (30%, papaya pulp (15%, spice extract (5%, and citric acid (0.1% were mixed in given proportion to prepare the blend with TSS of 15 °Brix. The product was bottled, pasteurized, and stored at room temperature. The quality characteristics and storage stability of the spiced beverage blend (SAGPB were compared with spiced papaya RTS beverage (SPB. Periodic analysis was carried out up to five months for various physicochemical parameters, sugar profile, bioactive compounds, microbial quality, instrumental color, and sensory acceptability. The SAGPB exhibited superior quality characteristics compared to SPB both in fresh and in stored samples. The SPB was acceptable up to four months and SAGPB for five months. The results indicate that nutraceutical rich AG could be successfully utilized to develop functional fruit beverages with improved quality and shelf life.

  11. Within treatment therapeutic alliance ratings profiles predict posttreatment frequency of alcohol use.

    Science.gov (United States)

    Prince, Mark A; Connors, Gerard J; Maisto, Stephen A; Dearing, Ronda L

    2016-03-01

    Although past research has demonstrated a positive relationship between the therapeutic alliance (TA) and improved drinking outcomes, specific aspects of the alliance have received less attention. In this study, we examined the association between alliance characteristics during treatment and 4-month follow-up drinking reports. Sixty-five treatment-seeking alcohol dependent clients who participated in 12 weeks of individual outpatient treatment provided weekly TA ratings during treatment and reported on pretreatment, during treatment, and posttreatment alcohol use. Latent profile analysis was conducted to discern distinct profiles of client and therapist ratings of therapeutic alliance with similar alliance characteristics. TA profiles were based on clients' and therapists' mean alliance rating, minimum alliance rating, maximum alliance rating, the range of alliance ratings, and the difference in session number between maximum and minimum alliance ratings. One- through 4-class models were fit to the data. Model fit was judged by comparative fit indices, substantive interpretability, and parsimony. Wald tests of mean equality determined whether classes differed on follow-up percentage of days abstinent (PDA) at 4-months posttreatment. Three-profile solutions provided the best fit for both client and therapist ratings of the therapeutic alliance. Client alliance rating profiles predicted drinking in the follow-up period, but therapist rating profiles did not. These results suggest that distinct profiles of the therapeutic alliance can be identified and that client alliance rating profiles are associated with frequency of alcohol use following outpatient treatment. (c) 2016 APA, all rights reserved).

  12. Technical player profiles related to the physical fitness of young female volleyball players predict team performance.

    Science.gov (United States)

    Dávila-Romero, C; Hernández-Mocholí, M A; García-Hermoso, A

    2015-03-01

    This study is divided into three sequential stages: identification of fitness and game performance profiles (individual player performance), an assessment of the relationship between these profiles, and an assessment of the relationship between individual player profiles and team performance during play (in championship performance). The overall study sample comprised 525 (19 teams) female volleyball players aged 12-16 years and a subsample (N.=43) used to examine study aims one and two was selected from overall sample. Anthropometric, fitness and individual player performance (actual game) data were collected in the subsample. These data were analyzed through clustering methods, ANOVA and independence chi-square test. Then, we investigated whether the proportion of players with the highest individual player performance profile might predict a team's results in the championship. Cluster analysis identified three volleyball fitness profiles (high, medium, and low) and two individual player performance profiles (high and low). The results showed a relationship between both types of profile (fitness and individual player performance). Then, linear regression revealed a moderate relationship between the number of players with a high volleyball fitness profile and a team's results in the championship (R2=0.23). The current study findings may enable coaches and trainers to manage training programs more efficiently in order to obtain tailor-made training, identify volleyball-specific physical fitness training requirements and reach better results during competitions.

  13. Prediction of Facial Profile Based on Morphometric Measurements and Profile Characteristics of Permanent Maxillary Central Incisor Teeth

    Directory of Open Access Journals (Sweden)

    N Raghavendra

    2015-01-01

    Full Text Available The computation of facial profile from dental morphometrics has been a subject of great interest in forensic odontology. The use of teeth to draw a profile and facial features is valuable in times of mass disasters when body remains are unavailable due to extreme destruction. This study aims to identify and evaluate applicable parameters in the permanent maxillary central incisors and the face of an individual. A correlation of these parameters establishes a mathematical equation that further charts a tooth-facial profile table. Thirty soft and hard tissue landmarks on the face in the frontal and the lateral profiles (using standardized photographs and seven landmarks on the facial/labial surface of the clinical crown of the permanent maxillary central incisor (using casts of the maxilla were identified for the study. Based on these, a set of eight horizontal and seven vertical parameters on the face and four parameters on the tooth were created for the assessment. Internal and external correlations between the two were carried out and statistically analyzed. A logistic regression was made to predict the probability of the parameters most likely to be reproduced in the creation of the facial profile, based on tooth morphometrics. The results indicated a definite correlation between the facial and the tooth parameters. Among the multiple parameters, a definite correlation in the horizontal dimension could be established between the mouth width and the mesiodistal width (MDW of the tooth. In the vertical dimension, a definite relationship existed between the crown height of the tooth and the width of the midface (zygoma-mandible. There exist divergences in the correlation of tooth and facial parameters.

  14. Exploring Stability and Change in Preschool Teachers' Shared Book Reading Verbal Language Profiles across One Semester

    Science.gov (United States)

    Bales, Mary K. Cockburn

    2013-01-01

    This study explored preschool teachers' verbal language profiles during shared book reading sessions. The verbal language profiles were comprised of a combination of instructional and management strategies both at the fall and winter time points. Latent profile and transition analyses were used to explore the profiles identified in the study's…

  15. The influence of profiled ceilings on sports hall acoustics : Ground effect predictions and scale model measurements

    NARCIS (Netherlands)

    Wattez, Y.C.M.; Tenpierik, M.J.; Nijs, L.

    2018-01-01

    Over the last few years, reverberation times and sound pressure levels have been measured in many sports halls. Most of these halls, for instance those made from stony materials, perform as predicted. However, sports halls constructed with profiled perforated steel roof panels have an unexpected

  16. Profiling healthy eaters: determining factors that predict healthy eating practices among Dutch adults

    NARCIS (Netherlands)

    Swan, E.; Bouwman, L.; Hiddink, G.J.; Aarts, N.; Koelen, M.

    2015-01-01

    Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's

  17. Profiling healthy eaters. Determining factors that predict healthy eating practices among Dutch adults

    NARCIS (Netherlands)

    Swan, E.C.; Bouwman, L.I.; Hiddink, G.J.; Aarts, N.; Koelen, M.

    2015-01-01

    Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's

  18. The use of background and ability profiles to predict college student outcomes.

    Science.gov (United States)

    Schmitt, Neal; Oswald, Frederick L; Kim, Brian H; Imus, Anna; Merritt, Stephanie; Friede, Alyssa; Shivpuri, Smriti

    2007-01-01

    To determine whether profiles of predictor variables provide incremental prediction of college student outcomes, the authors 1st applied an empirical clustering method to profiles based on the scores of 2,771 entering college students on a battery of biographical data and situational judgment measures, along with SAT and American College Test scores and high school grade point average, which resulted in 5 student groups. Performance of the students in these clusters was meaningfully different on a set of external variables, including college grade point average, self-rated performance, class absenteeism, organizational citizenship behavior, intent to quit their university, and satisfaction with college. The 14 variables in the profile were all significantly correlated with 1 or more of the outcome measures; however, nonlinear prediction of these outcomes on the basis of cluster membership did not add incrementally to a linear-regression-based combination of these 14 variables as predictors. 2007 APA, all rights reserved

  19. First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Ceder, Gerbrand [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials and Engineering

    2018-01-28

    Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

  20. A protein structural classes prediction method based on predicted secondary structure and PSI-BLAST profile.

    Science.gov (United States)

    Ding, Shuyan; Li, Yan; Shi, Zhuoxing; Yan, Shoujiang

    2014-02-01

    Knowledge of protein secondary structural classes plays an important role in understanding protein folding patterns. In this paper, 25 features based on position-specific scoring matrices are selected to reflect evolutionary information. In combination with other 11 rational features based on predicted protein secondary structure sequences proposed by the previous researchers, a 36-dimensional representation feature vector is presented to predict protein secondary structural classes for low-similarity sequences. ASTRALtraining dataset is used to train and design our method, other three low-similarity datasets ASTRALtest, 25PDB and 1189 are used to test the proposed method. Comparisons with other methods show that our method is effective to predict protein secondary structural classes. Stand alone version of the proposed method (PSSS-PSSM) is written in MATLAB language and it can be downloaded from http://letsgob.com/bioinfo_PSSS_PSSM/. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  1. Infants, mothers, and dyadic contributions to stability and prediction of social stress response at 6 months.

    Science.gov (United States)

    Provenzi, Livio; Olson, Karen L; Montirosso, Rosario; Tronick, Ed

    2016-01-01

    The study of infants' interactive style and social stress response to repeated stress exposures is of great interest for developmental and clinical psychologists. Stable maternal and dyadic behavior is critical to sustain infants' development of an adaptive social stress response, but the association between infants' interactive style and social stress response has received scant attention in previous literature. In the present article, overtime stability of infant, maternal, and dyadic behaviors was measured across 2 social stress (i.e., Face-to-Face Still-Face, FFSF) exposures, separated by 15 days. Moreover, infant, maternal, and dyadic behaviors were simultaneously assessed as predictors of infants' social stress to both FFSF exposures. Eighty-one mother-infant dyads underwent the FFSF twice, at 6 months (Exposure 1: the first social stress) and at 6 months and 15 days (Exposure 2: repeated social stress). Infant and mother behavior and dyadic synchrony were microanalytically coded. Overall, individual behavioral stability emerged between FFSF exposures. Infants' response to the first stress was predicted by infant behavior during Exposure 1 Play. Infants' response to the repeated social stress was predicted by infants' response to the first exposure to the Still-Face and by infants' behavior and dyadic synchrony during Exposure 2 Play. Findings reveal stability for individual, but not for dyadic, behavior between 2 social stress exposures at 6 months. Infants' response to repeated social stress was predicted by infants' earlier stress response, infants' own behavior in play, and dyadic synchrony. No predictive effects of maternal behavior were found. Insights for research and clinical work are discussed. (c) 2015 APA, all rights reserved).

  2. High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABER-TOOTH.

    Science.gov (United States)

    Teichert, Florian; Minning, Jonas; Bastolla, Ugo; Porto, Markus

    2010-05-14

    Protein alignments are an essential tool for many bioinformatics analyses. While sequence alignments are accurate for proteins of high sequence similarity, they become unreliable as they approach the so-called 'twilight zone' where sequence similarity gets indistinguishable from random. For such distant pairs, structure alignment is of much better quality. Nevertheless, sequence alignment is the only choice in the majority of cases where structural data is not available. This situation demands development of methods that extend the applicability of accurate sequence alignment to distantly related proteins. We develop a sequence alignment method that combines the prediction of a structural profile based on the protein's sequence with the alignment of that profile using our recently published alignment tool SABERTOOTH. In particular, we predict the contact vector of protein structures using an artificial neural network based on position-specific scoring matrices generated by PSI-BLAST and align these predicted contact vectors. The resulting sequence alignments are assessed using two different tests: First, we assess the alignment quality by measuring the derived structural similarity for cases in which structures are available. In a second test, we quantify the ability of the significance score of the alignments to recognize structural and evolutionary relationships. As a benchmark we use a representative set of the SCOP (structural classification of proteins) database, with similarities ranging from closely related proteins at SCOP family level, to very distantly related proteins at SCOP fold level. Comparing these results with some prominent sequence alignment tools, we find that SABERTOOTH produces sequence alignments of better quality than those of Clustal W, T-Coffee, MUSCLE, and PSI-BLAST. HHpred, one of the most sophisticated and computationally expensive tools available, outperforms our alignment algorithm at family and superfamily levels, while the use of

  3. High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABER-TOOTH

    Directory of Open Access Journals (Sweden)

    Bastolla Ugo

    2010-05-01

    Full Text Available Abstract Background Protein alignments are an essential tool for many bioinformatics analyses. While sequence alignments are accurate for proteins of high sequence similarity, they become unreliable as they approach the so-called 'twilight zone' where sequence similarity gets indistinguishable from random. For such distant pairs, structure alignment is of much better quality. Nevertheless, sequence alignment is the only choice in the majority of cases where structural data is not available. This situation demands development of methods that extend the applicability of accurate sequence alignment to distantly related proteins. Results We develop a sequence alignment method that combines the prediction of a structural profile based on the protein's sequence with the alignment of that profile using our recently published alignment tool SABERTOOTH. In particular, we predict the contact vector of protein structures using an artificial neural network based on position-specific scoring matrices generated by PSI-BLAST and align these predicted contact vectors. The resulting sequence alignments are assessed using two different tests: First, we assess the alignment quality by measuring the derived structural similarity for cases in which structures are available. In a second test, we quantify the ability of the significance score of the alignments to recognize structural and evolutionary relationships. As a benchmark we use a representative set of the SCOP (structural classification of proteins database, with similarities ranging from closely related proteins at SCOP family level, to very distantly related proteins at SCOP fold level. Comparing these results with some prominent sequence alignment tools, we find that SABERTOOTH produces sequence alignments of better quality than those of Clustal W, T-Coffee, MUSCLE, and PSI-BLAST. HHpred, one of the most sophisticated and computationally expensive tools available, outperforms our alignment algorithm at

  4. Vapor Pressure and Predicted Stability of American Contact Dermatitis Society Core Allergens.

    Science.gov (United States)

    Jou, Paul C; Siegel, Paul D; Warshaw, Erin M

    2016-01-01

    Accurate patch testing is reliant on proper preparation of patch test allergens. The stability of patch test allergens is dependent on several factors including vapor pressure (VP). This investigation reviews the VP of American Contact Dermatitis Society Core Allergens and compares stability predictions based on VP with those established through clinical testing. Standard references were accessed for determining VP in millimeters of mercury and associated temperature in degrees celsius. If multiple values were listed, VP at temperatures that most approximate indoor storage conditions (20°C and 25°C) were chosen. For mixes, the individual component with the highest VP was chosen as the overall VP, assuming that the most volatile substance would evaporate first. Antigens were grouped into low (≤0.001 mm Hg), moderate (0.001 mm Hg), and high (≥1 mm Hg) volatility using arbitrary cutoff values. This review is consistent with previously reported data on formaldehyde, acrylates, and fragrance material instability. Given lack of testing data, VP can be useful in predicting patch test compound stability. Measures such as air-tight multidose reagent containers, sealed single-application dispensers, preparation of patches immediately before application, and storage at lower temperatures may remedy some of these issues.

  5. Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

    Science.gov (United States)

    Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

    2015-09-01

    Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

  6. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

    Directory of Open Access Journals (Sweden)

    Liao Li

    2010-10-01

    Full Text Available Abstract Background Protein-protein interaction (PPI plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs, based on domains represented as interaction profile hidden Markov models (ipHMM where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB. Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD. Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure, an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on

  7. Natural Analoges as a Check of Predicted Drift Stability at Yucca Mountain, Nevada

    Energy Technology Data Exchange (ETDEWEB)

    J. Stuckless

    2006-03-10

    Calculations made by the U.S. Department of Energy's Yucca Mountain Project as part of the licensing of a proposed geologic repository (in southwestern Nevada) for the disposal of high-level radioactive waste, predict that emplacement tunnels will remain open with little collapse long after ground support has disintegrated. This conclusion includes the effects of anticipated seismic events. Natural analogues cannot provide a quantitative test of this conclusion, but they can provide a reasonableness test by examining the natural and anthropogenic examples of stability of subterranean openings. Available data from a variety of sources, combined with limited observations by the author, show that natural underground openings tend to resist collapse for millions of years and that anthropogenic subterranean openings have remained open from before recorded history through today. This stability is true even in seismically active areas. In fact, the archaeological record is heavily skewed toward preservation of underground structures relative to those found at the surface.

  8. Analytical Prediction of the Spin Stabilized Satellite's Attitude Using The Solar Radiation Torque

    Science.gov (United States)

    Motta, G. B.; Carvalho, M. V.; Zanardi, M. C.

    2013-10-01

    The aim of this paper is to present an analytical solution for the spin motion equations of spin-stabilized satellite considering only the influence of solar radiation torque. The theory uses a cylindrical satellite on a circular orbit and considers that the satellite is always illuminated. The average components of this torque were determined over an orbital period. These components are substituted in the spin motion equations in order to get an analytical solution for the right ascension and declination of the satellite spin axis. The time evolution for the pointing deviation of the spin axis was also analyzed. These solutions were numerically implemented and compared with real data of the Brazilian Satellite of Data Collection - SCD1 an SCD2. The results show that the theory has consistency and can be applied to predict the spin motion of spin-stabilized artificial satellites.

  9. VfoldCPX Server: Predicting RNA-RNA Complex Structure and Stability.

    Science.gov (United States)

    Xu, Xiaojun; Chen, Shi-Jie

    RNA-RNA interactions are essential for genomic RNA dimerization, mRNA splicing, and many RNA-related gene expression and regulation processes. The prediction of the structure and folding stability of RNA-RNA complexes is a problem of significant biological importance and receives substantial interest in the biological community. The VfoldCPX server provides a new web interface to predict the two-dimensional (2D) structures of RNA-RNA complexes from the nucleotide sequences. The VfoldCPX server has several novel advantages including the ability to treat RNAs with tertiary contacts (crossing base pairs) such as loop-loop kissing interactions and the use of physical loop entropy parameters. Based on a partition function-based algorithm, the server enables prediction for structure with and without tertiary contacts. Furthermore, the server outputs a set of energetically stable structures, ranked by their stabilities. The results allow users to gain extensive physical insights into RNA-RNA interactions and their roles in RNA function. The web server is freely accessible at "http://rna.physics.missouri.edu/vfoldCPX".

  10. Longitudinal stability and predictability of sexual perceptions, intentions, and behaviors among early adolescent African-Americans.

    Science.gov (United States)

    Stanton, B F; Li, X; Black, M M; Ricardo, I; Galbraith, J; Feigelman, S; Kaljee, L

    1996-01-01

    To assess the stability and predictability of perceptions, intentions, and behaviors regarding intended sexual intercourse and condom use. One hundred and nineteen African-American youth aged 9-15 years living in urban public housing provided information at baseline and 6 months later using a theory-based and culturally- and developmentally-tailored instrument assessing perceptions, intentions, and sexual behaviors. Over the 6-month study interval, individual behaviors, intentions, and perceptions demonstrated considerable stability. Intentions regarding sexual intercourse in the next half-year were predictive of subsequent coitus among the entire cohort and among the subset who were virgins at baseline. Youth who thought it likely that they would be sexually-active in the next 6 months were at significantly elevated risk of doing so, compared to youth who were uncertain or thought coitus unlikely. However, intentions regarding future coitus among the subset of youth who were sexually-experienced at baseline were not predictive of future coital behavior. These data suggest that social cognitive behavioral models that incorporate intentions and perceptions are appropriate as the theoretical basis for interventions targeting these young adolescents.

  11. Longitudinal prediction and concurrent functioning of adolescent girls demonstrating various profiles of dating violence and victimization.

    Science.gov (United States)

    Chiodo, Debbie; Crooks, Claire V; Wolfe, David A; McIsaac, Caroline; Hughes, Ray; Jaffe, Peter G

    2012-08-01

    Adolescent girls are involved in physical dating violence as both perpetrators and victims, and there are negative consequences associated with each of these behaviors. This article used a prospective design with 519 girls dating in grade 9 to predict profiles of dating violence in grade 11 based on relationships with families of origin (child maltreatment experiences, harsh parenting), and peers (harassment, delinquency, relational aggression). In addition, dating violence profiles were compared on numerous indices of adjustment (school connectedness, grades, self-efficacy and community connectedness) and maladjustment (suicide attempts, distress, delinquency, sexual behavior) for descriptive purposes. The most common profile was no dating violence (n = 367) followed by mutual violence (n = 81). Smaller numbers of girls reported victimization or perpetration only (ns = 39 and 32, respectively). Predicting grade 11 dating violence profile membership from grade 9 relationships was limited, although delinquency, parental rejection, and sexual harassment perpetration predicted membership to the mutually violent group, and delinquency predicted the perpetrator-only group. Compared to the non-violent group, the mutually violent girls in grade 11 had lower grades, poorer self-efficacy, and lower school connectedness and community involvement. Furthermore, they had higher rates of peer aggression and delinquency, were less likely to use condoms and were much more likely to have considered suicide. There were fewer differences among the profiles for girls involved with dating violence. In addition, the victims-only group reported higher rates of sexual intercourse, comparable to the mutually violent group and those involved in nonviolent relationships. Implications for prevention and intervention are highlighted.

  12. Prediction of opioid dose in cancer pain patients using genetic profiling

    DEFF Research Database (Denmark)

    Olesen, Anne Estrup; Grønlund, Debbie; Gram, Mikkel

    2018-01-01

    OBJECTIVE: Use of opioids for pain management has increased over the past decade; however, inadequate analgesic response is common. Genetic variability may be related to opioid efficacy, but due to the many possible combinations and variables, statistical computations may be difficult. This study...... investigated whether data processing with support vector machine learning could predict required opioid dose in cancer pain patients, using genetic profiling. Eighteen single nucleotide polymorphisms (SNPs) within the µ and δ opioid receptor genes and the catechol-O-methyltransferase gene were selected...... dose using genetic profiling....

  13. Noun and Verb Production in Maternal and Child Language: Continuity, Stability, and Prediction across the Second Year of Life

    Science.gov (United States)

    Longobardi, Emiddia; Spataro, Pietro; Putnick, Diane L.; Bornstein, Marc H.

    2016-01-01

    The present study examined continuity/discontinuity and stability/instability of noun and verb production measures in 30 child-mother dyads observed at 16 and 20 months, and predictive relations with the acquisition of nouns and verbs at 24 months. Children exhibited significant discontinuity and robust stability in the frequency of nouns and…

  14. Predicting the Genetic Stability of Engineered DNA Sequences with the EFM Calculator.

    Science.gov (United States)

    Jack, Benjamin R; Leonard, Sean P; Mishler, Dennis M; Renda, Brian A; Leon, Dacia; Suárez, Gabriel A; Barrick, Jeffrey E

    2015-08-21

    Unwanted evolution can rapidly degrade the performance of genetically engineered circuits and metabolic pathways installed in living organisms. We created the Evolutionary Failure Mode (EFM) Calculator to computationally detect common sources of genetic instability in an input DNA sequence. It predicts two types of mutational hotspots: deletions mediated by homologous recombination and indels caused by replication slippage on simple sequence repeats. We tested the performance of our algorithm on genetic circuits that were previously redesigned for greater evolutionary reliability and analyzed the stability of sequences in the iGEM Registry of Standard Biological Parts. More than half of the parts in the Registry are predicted to experience >100-fold elevated mutation rates due to the inclusion of unstable sequence configurations. We anticipate that the EFM Calculator will be a useful negative design tool for avoiding volatile DNA encodings, thereby increasing the evolutionary lifetimes of synthetic biology devices.

  15. Uniformity of spherical shock wave dynamically stabilized by two successive laser profiles in direct-drive inertial confinement fusion implosions

    Energy Technology Data Exchange (ETDEWEB)

    Temporal, M., E-mail: mauro.temporal@hotmail.com [Centre de Mathématiques et de Leurs Applications, ENS Cachan and CNRS, 61 Av. du President Wilson, F-94235 Cachan Cedex (France); Canaud, B. [CEA, DIF, F-91297 Arpajon Cedex (France); Garbett, W. J. [AWE plc, Aldermaston, Reading, Berkshire RG7 4PR (United Kingdom); Ramis, R. [ETSI Aeronáutica y del Espacio, Universidad Politécnica de Madrid, 28040 Madrid (Spain)

    2015-10-15

    The implosion uniformity of a directly driven spherical inertial confinement fusion capsule is considered within the context of the Laser Mégajoule configuration. Two-dimensional (2D) hydrodynamic simulations have been performed assuming irradiation with two laser beam cones located at 49° and 131° with respect to the axis of symmetry. The laser energy deposition causes an inward shock wave whose surface is tracked in time, providing the time evolution of its non-uniformity. The illumination model has been used to optimize the laser intensity profiles used as input in the 2D hydro-calculations. It is found that a single stationary laser profile does not maintain a uniform shock front over time. To overcome this drawback, it is proposed to use two laser profiles acting successively in time, in order to dynamically stabilize the non-uniformity of the shock front.

  16. Theoretical prediction of Reynolds stresses and velocity profiles for barotropic turbulent jets

    Science.gov (United States)

    Woillez, E.; Bouchet, F.

    2017-06-01

    It is extremely uncommon to be able to predict the velocity profile of a turbulent flow. In two-dimensional flows, atmosphere dynamics, and plasma physics, large-scale coherent jets are created through inverse energy transfers from small scales to the largest scales of the flow. We prove that in the limits of vanishing energy injection, vanishing friction, and small-scale forcing, the velocity profile of a jet obeys an equation independently of the details of the forcing. We find another general relation for the maximal curvature of a jet and we give strong arguments to support the existence of a hydrodynamic instability at the point with minimal jet velocity. Those results are the first computations of Reynolds stresses and self-consistent velocity profiles from the turbulent dynamics, and the first consistent analytic theory of zonal jets in barotropic turbulence.

  17. Prediction of metastasis from low-malignant breast cancer by gene expression profiling

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

    2007-01-01

    examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...... and 77% specificity. The classifier was also validated in an independent group of high-risk tumors resulting in comparable performance of HUMAC32 and a 70-gene classifier developed for this group. Furthermore, the 70-gene signature was tested in our low- and intermediate-risk samples. The results...

  18. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

    Directory of Open Access Journals (Sweden)

    Rianon Zaman

    2017-01-01

    Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  19. Prediction of crank torque and pedal angle profiles during pedaling movements by biomechanical optimization

    DEFF Research Database (Denmark)

    Farahani, Saeed Davoudabadi; Bertucci, William; Andersen, Michael Skipper

    2015-01-01

    and constraints. The cost function and the constraints typically express performance, comfort, injury risk, fatigue, muscle load, joint forces and other physiological properties derived from the detailed musculoskeletal analysis. A physiology-based cost function that expresses the integral effort over a cycle...... to predict the motion pattern and crank torque was used. An experiment was conducted on a group of eight highly trained male cyclists to compare experimental observations to the simulation results. The proposed performance criterion predicts realistic crank torque profiles and ankle movement patterns....

  20. Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

    Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

  1. Ozone Mapping and Profiler Suite: using mission performance data to refine predictive contamination modeling

    Science.gov (United States)

    Devaud, Genevieve; Jaross, Glen

    2014-09-01

    On October 28, 2011, the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched at Vandenberg Air Force base aboard a United Launch Alliance Delta II rocket. Included among the five instruments was the Ozone Mapping and Profiler Suite (OMPS), an advanced suite of three hyperspectral instruments built by Ball Aerospace and Technologies Corporation (BATC) for the NASA Goddard Space Flight Center. Molecular transport modeling is used to predict optical throughput changes due to contaminant accumulation to ensure performance margin to End Of Life. The OMPS Nadir Profiler, operating at the lowest wavelengths of 250 - 310 nm, is most sensitive to contaminant accumulation. Geometry, thermal profile and material properties must be accurately modeled in order to have confidence in the results, yet it is well known that the complex chemistry and process dependent variability of aerospace materials presents a substantial challenge to the modeler. Assumptions about the absorption coefficients, desorption and diffusion kinetics of outgassing species from polymeric materials dramatically affect the model predictions, yet it is rare indeed that on-mission data is analyzed at a later date as a means to compare with modeling results. Optical throughput measurements for the Ozone and Mapping Profiler Suite on the Suomi NPP Satellite indicate that optical throughput degradation between day 145 and day 858 is less than 0.5%. We will show how assumptions about outgassing rates and desorption energies, in particular, dramatically affect the modeled optical throughput and what assumptions represent the on-orbit data.

  2. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans.

    Science.gov (United States)

    Rhee, Eugene P; Cheng, Susan; Larson, Martin G; Walford, Geoffrey A; Lewis, Gregory D; McCabe, Elizabeth; Yang, Elaine; Farrell, Laurie; Fox, Caroline S; O'Donnell, Christopher J; Carr, Steven A; Vasan, Ramachandran S; Florez, Jose C; Clish, Clary B; Wang, Thomas J; Gerszten, Robert E

    2011-04-01

    Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

  3. Machine learning integration for predicting the effect of single amino acid substitutions on protein stability

    Directory of Open Access Journals (Sweden)

    Haliloğlu Türkan

    2009-10-01

    Full Text Available Abstract Background Computational prediction of protein stability change due to single-site amino acid substitutions is of interest in protein design and analysis. We consider the following four ways to improve the performance of the currently available predictors: (1 We include additional sequence- and structure-based features, namely, the amino acid substitution likelihoods, the equilibrium fluctuations of the alpha- and beta-carbon atoms, and the packing density. (2 By implementing different machine learning integration approaches, we combine information from different features or representations. (3 We compare classification vs. regression methods to predict the sign vs. the output of stability change. (4 We allow a reject option for doubtful cases where the risk of misclassification is high. Results We investigate three different approaches: early, intermediate and late integration, which respectively combine features, kernels over feature subsets, and decisions. We perform simulations on two data sets: (1 S1615 is used in previous studies, (2 S2783 is the updated version (as of July 2, 2009 extracted also from ProTherm. For S1615 data set, our highest accuracy using both sequence and structure information is 0.842 on cross-validation and 0.904 on testing using early integration. Newly added features, namely, local compositional packing and the mobility extent of the mutated residues, improve accuracy significantly with intermediate integration. For S2783 data set, we also train regression methods to estimate not only the sign but also the amount of stability change and apply risk-based classification to reject when the learner has low confidence and the loss of misclassification is high. The highest accuracy is 0.835 on cross-validation and 0.832 on testing using only sequence information. The percentage of false positives can be decreased to less than 0.005 by rejecting 10 per cent using late integration. Conclusion We find that in both

  4. Presurgical symptom profiles predict quality of life 2 years after surgery in women with breast cancer.

    Science.gov (United States)

    Chen, Mei-Ling; Liu, Li-Ni; Miaskowski, Christine; Chen, Shin-Cheh; Lin, Yung-Chang; Wang, Jong-Shyan

    2016-01-01

    Higher symptom burden in oncology patients is associated with poorer quality of life (QOL). However, the long-term predictive relationship between pre-treatment symptom profiles and QOL is unknown. The aim of this study was to identify subgroups of breast cancer patients based on their presurgical symptom profiles and to examine the predictive effect of group membership on QOL 2 years after surgery. Data were analyzed from a longitudinal study of women's (N = 198) symptoms after breast cancer surgery. Patient subgroups were identified by latent class analysis based on presurgical severity of five symptoms (i.e., attentional and physical fatigue, sleep disturbance, depression, and anxiety). Among these 198 women, quality of life 2 years after surgery was available for 97. Group differences in QOL were examined by general linear models. We identified four distinct patient groups. Group A (All Low) had low levels of all symptoms. Group B (Low Fatigue and Moderate Mood) was characterized by low attentional and physical fatigue but moderate sleep disturbance, depression, and anxiety. Group C (All Moderate) was characterized by moderate levels of all five symptoms. Group D was characterized by moderate attentional and physical fatigue and severe sleep disturbance, depression, and anxiety (Moderate Fatigue and High Mood). Group D had significantly lower overall QOL scores 2 years after surgery than Group A (p = 0.002). Breast cancer patients' presurgical symptom profile had a long-term predictive effect on QOL. Routine assessment of patients' pre-treatment symptom is suggested to identify high risk group.

  5. Stability profile of flavour-active ester compounds in ale and lager ...

    African Journals Online (AJOL)

    ... while ethyl decanoate was the least stable, with 36.77% decrease in concentration observed at room temperature. Results obtained in this study can be helpful in developing appropriate technological process to control the stability of these important flavour esters in beer. Keywords: Esters, stability, storage temperature, ...

  6. Latent profiles of nonresidential father engagement six years after divorce predict long-term offspring outcomes.

    Science.gov (United States)

    Modecki, Kathryn Lynn; Hagan, Melissa J; Sandler, Irwin; Wolchik, Sharlene A

    2015-01-01

    This study examined profiles of nonresidential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) 6 to 8 years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, 9 years later. Parental divorce occurred during late childhood to early adolescence; indicators of nonresidential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed 9 years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes 9 years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother's remarriage, mother's income, and gender, age, and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems 9 years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long term. Implications of findings for policy and intervention are discussed.

  7. [Factors predicting sensory profile of 4 to 18 month old infants].

    Science.gov (United States)

    Pedrosa, Carina; Caçola, Priscila; Carvalhal, Maria Isabel Martins Mourão

    2015-01-01

    To identify environment factors predicting sensory profile of infants between 4 and 18 months old. This cross-sectional study evaluated 97 infants (40 females e 57 males), with a mean age of 1.05±0.32 years with the Test of Sensory Functions in Infants (TSFI) and also asked 97 parents and 11 kindergarten teachers of seven daycare centers to answer the Affordances in the Home Environment for Motor Development- Infant Scale (AHEMD-IS). The AHEMD-IS is a questionnaire that characterizes the opportunities in the home environment for infants between 3 and 18 months of age. We tested the association between affordances and the sensory profile of infants. Significant variables were entered into a regression model to determine predictors of sensory profile. The majority of infants (66%) had a normal sensory profile and 34% were at risk or deficit. Affordances in the home were classified as adequate and they were good in the studied daycare centers. The results of the regression revealed that only daily hours in daycare center and daycare outside space influenced the sensory profile of infants, in particular the Ocular-Motor Control component. The sensory profile of infants was between normal and at risk. While the family home offered adequate affordances for motor development, the daycare centers of the infants involved demonstrated a good quantity and quality of affordances. Overall, we conclude that daily hours in the daycare center and daycare outside space were predictors of the sensory profile, particular on Ocular-Motor Control component. Copyright © 2015 Associação de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

  8. Factors predicting sensory profile of 4 to 18 month old infants

    Science.gov (United States)

    Pedrosa, Carina; Caçola, Priscila; Carvalhal, Maria Isabel Martins Mourão

    2015-01-01

    OBJECTIVE: To identify environment factors predicting sensory profile of infants between 4 and 18 months old. METHODS: This cross-sectional study evaluated 97 infants (40 females e 57 males), with a mean age of 1.05±0.32 years with the Test of Sensory Functions in Infants (TSFI) and also asked 97 parents and 11 kindergarten teachers of seven daycare centers to answer the Affordances in the Home Environment for Motor Development-Infant Scale (AHEMD-IS). The AHEMD-IS is a questionnaire that characterizes the opportunities in the home environment for infants between 3 and 18 months of age. We tested the association between affordances and the sensory profile of infants. Significant variables were entered into a regression model to determine predictors of sensory profile. RESULTS: The majority of infants (66%) had a normal sensory profile and 34% were at risk or deficit. Affordances in the home were classified as adequate and they were good in the studied daycare centers. The results of the regression revealed that only daily hours in daycare center and daycare outside space influenced the sensory profile of infants, in particular the Ocular-Motor Control component. CONCLUSIONS: The sensory profile of infants was between normal and at risk. While the family home offered adequate affordances for motor development, the daycare centers of the infants involved demonstrated a good quantity and quality of affordances. Overall, we conclude that daily hours in the daycare center and daycare outside space were predictors of the sensory profile, particular on Ocular-Motor Control component. PMID:25887929

  9. Factors predicting sensory profile of 4 to 18 month old infants

    Directory of Open Access Journals (Sweden)

    Carina Pedrosa

    2015-06-01

    Full Text Available OBJECTIVE: To identify environment factors predicting sensory profile of infants between 4 and 18 months old. METHODS: This cross-sectional study evaluated 97 infants (40 females e 57 males, with a mean age of 1.05±0.32 years with the Test of Sensory Functions in Infants (TSFI and also asked 97 parents and 11 kindergarten teachers of seven daycare centers to answer the Affordances in the Home Environment for Motor Development-Infant Scale (AHEMD-IS. The AHEMD-IS is a questionnaire that characterizes the opportunities in the home environment for infants between 3 and 18 months of age. We tested the association between affordances and the sensory profile of infants. Significant variables were entered into a regression model to determine predictors of sensory profile. RESULTS: The majority of infants (66% had a normal sensory profile and 34% were at risk or deficit. Affordances in the home were classified as adequate and they were good in the studied daycare centers. The results of the regression revealed that only daily hours in daycare center and daycare outside space influenced the sensory profile of infants, in particular the Ocular-Motor Control component. CONCLUSIONS: The sensory profile of infants was between normal and at risk. While the family home offered adequate affordances for motor development, the daycare centers of the infants involved demonstrated a good quantity and quality of affordances. Overall, we conclude that daily hours in the daycare center and daycare outside space were predictors of the sensory profile, particular on Ocular-Motor Control component.

  10. Predicting Risk of Infection in Patients with Newly Diagnosed Multiple Myeloma: Utility of Immune Profiling

    Directory of Open Access Journals (Sweden)

    Benjamin W. Teh

    2017-10-01

    Full Text Available BackgroundA translational study in patients with myeloma to determine the utility of immune profiling to predict infection risk in patients with hematological malignancy was conducted.MethodsBaseline, end of induction, and maintenance peripheral blood mononuclear cells from 40 patients were evaluated. Immune cell populations and cytokines released from 1 × 106 cells/ml cultured in the presence of a panel of stimuli (cytomegalovirus, influenza, S. pneumoniae, phorbol myristate acetate/ionomycin and in media alone were quantified. Patient characteristics and infective episodes were captured from clinical records. Immunological variables associated with increased risk for infection in the 3-month period following sample collection were identified using univariate analysis (p < 0.05 and refined with multivariable analysis to define a predictive immune profile.Results525 stimulant samples with 19,950 stimulant–cytokine combinations across three periods were studied, including 61 episodes of infection. Mitogen-stimulated release of IL3 and IL5 were significantly associated with increased risk for subsequent infection during maintenance therapy. A lower Th1/Th2 ratio and higher cytokine response ratios for IL5 and IL13 during maintenance therapy were also significantly associated with increased risk for infection. On multivariable analysis, only IL5 in response to mitogen stimulation was predictive of infection. The lack of cytokine response and numerical value of immune cells were not predictive of infection.ConclusionProfiling cytokine release in response to mitogen stimulation can assist with predicting subsequent onset of infection in patients with hematological malignancy during maintenance therapy.

  11. Stabilization

    Directory of Open Access Journals (Sweden)

    Muhammad H. Al-Malack

    2016-07-01

    Full Text Available Fuel oil flyash (FFA produced in power and water desalination plants firing crude oils in the Kingdom of Saudi Arabia is being disposed in landfills, which increases the burden on the environment, therefore, FFA utilization must be encouraged. In the current research, the effect of adding FFA on the engineering properties of two indigenous soils, namely sand and marl, was investigated. FFA was added at concentrations of 5%, 10% and 15% to both soils with and without the addition of Portland cement. Mixtures of the stabilized soils were thoroughly evaluated using compaction, California Bearing Ratio (CBR, unconfined compressive strength (USC and durability tests. Results of these tests indicated that stabilized sand mixtures could not attain the ACI strength requirements. However, marl was found to satisfy the ACI strength requirement when only 5% of FFA was added together with 5% of cement. When the FFA was increased to 10% and 15%, the mixture’s strength was found to decrease to values below the ACI requirements. Results of the Toxicity Characteristics Leaching Procedure (TCLP, which was performed on samples that passed the ACI requirements, indicated that FFA must be cautiously used in soil stabilization.

  12. Dynamic Data-Driven Prediction of Lean Blowout in a Swirl-Stabilized Combustor

    Directory of Open Access Journals (Sweden)

    Soumalya Sarkar

    2015-09-01

    Full Text Available This paper addresses dynamic data-driven prediction of lean blowout (LBO phenomena in confined combustion processes, which are prevalent in many physical applications (e.g., land-based and aircraft gas-turbine engines. The underlying concept is built upon pattern classification and is validated for LBO prediction with time series of chemiluminescence sensor data from a laboratory-scale swirl-stabilized dump combustor. The proposed method of LBO prediction makes use of the theory of symbolic dynamics, where (finite-length time series data are partitioned to produce symbol strings that, in turn, generate a special class of probabilistic finite state automata (PFSA. These PFSA, called D-Markov machines, have a deterministic algebraic structure and their states are represented by symbol blocks of length D or less, where D is a positive integer. The D-Markov machines are constructed in two steps: (i state splitting, i.e., the states are split based on their information contents, and (ii state merging, i.e., two or more states (of possibly different lengths are merged together to form a new state without any significant loss of the embedded information. The modeling complexity (e.g., number of states of a D-Markov machine model is observed to be drastically reduced as the combustor approaches LBO. An anomaly measure, based on Kullback-Leibler divergence, is constructed to predict the proximity of LBO. The problem of LBO prediction is posed in a pattern classification setting and the underlying algorithms have been tested on experimental data at different extents of fuel-air premixing and fuel/air ratio. It is shown that, over a wide range of fuel-air premixing, D-Markov machines with D > 1 perform better as predictors of LBO than those with D = 1.

  13. A three-state prediction of single point mutations on protein stability changes

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    Rossi Ivan

    2008-03-01

    Full Text Available Abstract Background A basic question of protein structural studies is to which extent mutations affect the stability. This question may be addressed starting from sequence and/or from structure. In proteomics and genomics studies prediction of protein stability free energy change (ΔΔG upon single point mutation may also help the annotation process. The experimental ΔΔG values are affected by uncertainty as measured by standard deviations. Most of the ΔΔG values are nearly zero (about 32% of the ΔΔG data set ranges from −0.5 to 0.5 kcal/mole and both the value and sign of ΔΔG may be either positive or negative for the same mutation blurring the relationship among mutations and expected ΔΔG value. In order to overcome this problem we describe a new predictor that discriminates between 3 mutation classes: destabilizing mutations (ΔΔG1.0 kcal/mole and neutral mutations (−1.0≤ΔΔG≤1.0 kcal/mole. Results In this paper a support vector machine starting from the protein sequence or structure discriminates between stabilizing, destabilizing and neutral mutations. We rank all the possible substitutions according to a three state classification system and show that the overall accuracy of our predictor is as high as 56% when performed starting from sequence information and 61% when the protein structure is available, with a mean value correlation coefficient of 0.27 and 0.35, respectively. These values are about 20 points per cent higher than those of a random predictor. Conclusions Our method improves the quality of the prediction of the free energy change due to single point protein mutations by adopting a hypothesis of thermodynamic reversibility of the existing experimental data. By this we both recast the thermodynamic symmetry of the problem and balance the distribution of the available experimental measurements of free energy changes. This eliminates possible overestimations of the previously described methods trained on an

  14. Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

    Science.gov (United States)

    Mandal, Tanmay Kumar

    Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of

  15. On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations

    Energy Technology Data Exchange (ETDEWEB)

    Fayet, Guillaume [Laboratoire d' Electrochimie et Chimie Analytique, CNRS UMR-7575, Ecole Nationale Superieure de Chimie de Paris, 11 rue P. et M. Curie, 75231 Paris Cedex 05 (France); Institut National de l' Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte (France); Rotureau, Patricia, E-mail: patricia.rotureau@ineris.fr [Institut National de l' Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte (France); Joubert, Laurent; Adamo, Carlo [Laboratoire d' Electrochimie et Chimie Analytique, CNRS UMR-7575, Ecole Nationale Superieure de Chimie de Paris, 11 rue P. et M. Curie, 75231 Paris Cedex 05 (France)

    2009-11-15

    This work presents a new approach to predict thermal stability of nitroaromatic compounds based on quantum chemical calculations and on quantitative structure-property relationship (QSPR) methods. The data set consists of 22 nitroaromatic compounds of known decomposition enthalpy (taken as a macroscopic property related to explosibility) obtained from differential scanning calorimetry. Geometric, electronic and energetic descriptors have been selected and computed using density functional theory (DFT) calculation to describe the 22 molecules. First approach consisted in looking at their linear correlations with the experimental decomposition enthalpy. Molecular weight, electrophilicity index, electron affinity and oxygen balance appeared as the most correlated descriptors (respectively R{sup 2} = 0.76, 0.75, 0.71 and 0.64). Then multilinear regression was computed with these descriptors. The obtained model is a six-parameter equation containing descriptors all issued from quantum chemical calculations. The prediction is satisfactory with a correlation coefficient R{sup 2} of 0.91 and a predictivity coefficient R{sub cv}{sup 2} of 0.84 using a cross validation method.

  16. On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations.

    Science.gov (United States)

    Fayet, Guillaume; Rotureau, Patricia; Joubert, Laurent; Adamo, Carlo

    2009-11-15

    This work presents a new approach to predict thermal stability of nitroaromatic compounds based on quantum chemical calculations and on quantitative structure-property relationship (QSPR) methods. The data set consists of 22 nitroaromatic compounds of known decomposition enthalpy (taken as a macroscopic property related to explosibility) obtained from differential scanning calorimetry. Geometric, electronic and energetic descriptors have been selected and computed using density functional theory (DFT) calculation to describe the 22 molecules. First approach consisted in looking at their linear correlations with the experimental decomposition enthalpy. Molecular weight, electrophilicity index, electron affinity and oxygen balance appeared as the most correlated descriptors (respectively R(2)=0.76, 0.75, 0.71 and 0.64). Then multilinear regression was computed with these descriptors. The obtained model is a six-parameter equation containing descriptors all issued from quantum chemical calculations. The prediction is satisfactory with a correlation coefficient R(2) of 0.91 and a predictivity coefficient R(cv)(2) of 0.84 using a cross validation method.

  17. Prediction profiles for nutritional supplement use among young German elite athletes.

    Science.gov (United States)

    Dietz, Pavel; Ulrich, Rolf; Niess, Andreas; Best, Raymond; Simon, Perikles; Striegel, Heiko

    2014-12-01

    Nutritional supplements (NS) are defined as concentrated sources of nutrients and other substances that have a nutritional or physiological effect and that are used in high frequency among athletes. The study aimed to create a prediction profile for young elite athletes to identify those athletes who have a higher relative risk for using NS. The second objective was to examine the hypothesis that the consumption of NS paves a gateway for the use of illicit drugs and doping substances. A self-designed anonymous paper-and-pencil questionnaire was used to examine the prevalence of NS consumption, doping, and illicit drug use in elite athletes with a mean age of 17 years (SD = 4 years). Logistic regression analysis was employed to assess whether NS consumption can be predicted by independent variables (e.g., biographical data, training characteristics, drug consumption behavior) to create the prediction profile for NS use. 55% and 5% of the athletes (n = 536) responded positively to having used NS and illicit drugs, respectively. Nutritional supplement consumption was positively correlated with age (OR: 1.92; CI: 1.21 to 3.05), the desire to enhance performance to become an Olympic or World Champion (OR: 3.72; CI: 2.33 to 6.01), and being educated about NS (OR: 2.76; CI: 1.73 to 4.45). It was negatively correlated with training frequency (OR: 0.55; CI: 0.35 to 0.86) and the use of nicotine (OR: 0.29; CI: 0.1 to 0.74) but did not correlate with illicit drug use and alcohol consumption. The present results show that NS are used on a large scale in elite sports. The prediction profile presented in this article may help to identify those athletes who have a high risk for using NS to plan potential education and prevention models more individually.

  18. Computational analysis of epidermal growth factor receptor mutations predicts differential drug sensitivity profiles towards kinase inhibitors.

    Science.gov (United States)

    Akula, Sravani; Kamasani, Swapna; Sivan, SreeKanth; Manga, Vijjulatha; Vudem, Dashavantha Reddy; Kancha, Rama Krishna

    2018-01-21

    A significant proportion of lung cancer patients carry mutations in the epidermal growth factor receptor (EGFR) kinase domain. The presence of a deletion mutation in exon 19 or L858R point mutation in the EGFR kinase domain were shown to cause enhanced efficacy of inhibitor treatment in NSCLC patients. Several less frequent ("Uncommon") mutations in the EGFR kinase domain with potential implications in treatment response were also reported. The role of a limited number of uncommon mutations in drug sensitivity was experimentally verified. However, a huge number of these mutations remain uncharacterized for inhibitor sensitivity/resistance. A large scale computational analysis of clinically reported 298 point mutants of EGFR kinase domain has been performed and drug sensitivity profiles for each mutant towards seven kinase inhibitors has been determined by molecular docking. In addition, the relative inhibitor binding affinity (RIBA) towards each drug as compared to that of the ATP was calculated for each mutant. The inhibitor sensitivity profiles predicted in this study for a set of previously characterized mutants correlated well with the published clinical, experimental and computational data. Both the single and compound mutations displayed differential inhibitor sensitivity towards first and next generation kinase inhibitors. The present study provides predicted drug sensitivity profiles for a large panel of uncommon EGFR mutations towards multiple inhibitors which may help clinicians in deciding mutant-specific treatment strategies. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  19. A new metric of inclusive fitness predicts the human mortality profile.

    Directory of Open Access Journals (Sweden)

    Saul J Newman

    Full Text Available Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

  20. Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks

    Directory of Open Access Journals (Sweden)

    Ramanpreet Kaur

    2017-02-01

    Full Text Available Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.

  1. Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

    Science.gov (United States)

    Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

    2017-12-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

  2. Model Predictive Control with Integral Action for Current Density Profile Tracking in NSTX-U

    Science.gov (United States)

    Ilhan, Z. O.; Wehner, W. P.; Schuster, E.; Boyer, M. D.

    2016-10-01

    Active control of the toroidal current density profile may play a critical role in non-inductively sustained long-pulse, high-beta scenarios in a spherical torus (ST) configuration, which is among the missions of the NSTX-U facility. In this work, a previously developed physics-based control-oriented model is embedded in a feedback control scheme based on a model predictive control (MPC) strategy to track a desired current density profile evolution specified indirectly by a desired rotational transform profile. An integrator is embedded into the standard MPC formulation to reject various modeling uncertainties and external disturbances. Neutral beam powers, electron density, and total plasma current are used as actuators. The proposed MPC strategy incorporates various state and actuator constraints directly into the control design process by solving a constrained optimization problem in real-time to determine the optimal actuator requests. The effectiveness of the proposed controller in regulating the current density profile in NSTX-U is demonstrated in closed-loop nonlinear simulations. Supported by the US DOE under DE-AC02-09CH11466.

  3. Performance prediction of optical image stabilizer using SVM for shaker-free production line

    Science.gov (United States)

    Kim, HyungKwan; Lee, JungHyun; Hyun, JinWook; Lim, Haekeun; Kim, GyuYeol; Moon, HyukSoo

    2016-04-01

    Recent smartphones adapt the camera module with optical image stabilizer(OIS) to enhance imaging quality in handshaking conditions. However, compared to the non-OIS camera module, the cost for implementing the OIS module is still high. One reason is that the production line for the OIS camera module requires a highly precise shaker table in final test process, which increases the unit cost of the production. In this paper, we propose a framework for the OIS quality prediction that is trained with the support vector machine and following module characterizing features : noise spectral density of gyroscope, optically measured linearity and cross-axis movement of hall and actuator. The classifier was tested on an actual production line and resulted in 88% accuracy of recall rate.

  4. Should I Stay or Should I Go? Predicting Dating Relationship Stability from Four Aspects of Commitment

    Science.gov (United States)

    Rhoades, Galena K.; Stanley, Scott M.; Markman, Howard J.

    2010-01-01

    Many have argued that it is important to examine different aspects of commitment in romantic relationships, but few studies have done so. Using a large, national sample of unmarried adults in relationships (N = 1184), this study examined four aspects of relationship commitment and their associations with relationship adjustment and stability. We examined dedication (i.e., interpersonal commitment) as well as three types of constraint commitment: perceived constraints (e.g., social pressure to stay together or difficulty of termination procedures, measured using Stanley and Markman’s (1992) Commitment Inventory), material constraints (e.g., signing a lease, owning a pet), and felt constraint (i.e., feeling trapped). Cross-sectionally, these four facets of commitment were associated in expected directions with relationship adjustment, as well as perceived likelihood of relationship termination and of marriage. Longitudinally, each facet uniquely predicted relationship stability. More dedication, more material and perceived constraints and less felt constraint were uniquely associated with a higher likelihood of staying together over an eight-month period. PMID:20954764

  5. SDM: a server for predicting effects of mutations on protein stability.

    Science.gov (United States)

    Pandurangan, Arun Prasad; Ochoa-Montaño, Bernardo; Ascher, David B; Blundell, Tom L

    2017-05-19

    Here, we report a webserver for the improved SDM, used for predicting the effects of mutations on protein stability. As a pioneering knowledge-based approach, SDM has been highlighted as the most appropriate method to use in combination with many other approaches. We have updated the environment-specific amino-acid substitution tables based on the current expanded PDB (a 5-fold increase in information), and introduced new residue-conformation and interaction parameters, including packing density and residue depth. The updated server has been extensively tested using a benchmark containing 2690 point mutations from 132 different protein structures. The revised method correlates well against the hypothetical reverse mutations, better than comparable methods built using machine-learning approaches, highlighting the strength of our knowledge-based approach for identifying stabilising mutations. Given a PDB file (a Protein Data Bank file format containing the 3D coordinates of the protein atoms), and a point mutation, the server calculates the stability difference score between the wildtype and mutant protein. The server is available at http://structure.bioc.cam.ac.uk/sdm2. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Anterior Cruciate Ligament Tear: Reliability of MR Imaging to Predict Stability after Conservative Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Hye Won; Ahn, Jin Hwan; Ahn, Joong Mo; Yoon, Young Cheol; Hong, Hyun Pyo; Yoo, So Young; Kim, Seon Woo [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

    2007-06-15

    The aim of this study is to evaluate the reliability of MR imaging to predict the stability of the torn anterior cruciate ligament (ACL) after complete recovery of the ligament's continuity. Twenty patients with 20 knee injuries (13 males and 7 females; age range, 20 54) were enrolled in the study. The inclusion criteria were a positive history of acute trauma, diagnosis of the ACL tear by both the physical examination and the MR imaging at the initial presentation, conservative treatment, complete recovery of the continuity of the ligament on the follow up (FU) MR images and availability of the KT-2000 measurements. Two radiologists, who worked in consensus, graded the MR findings with using a 3-point system for the signal intensity, sharpness, straightness and the thickness of the healed ligament. The insufficiency of ACL was categorized into three groups according to the KT-2000 measurements. The statistic correlations between the grades of the MR findings and the degrees of ACL insufficiency were analyzed using the Cochran-Mantel-Haenszel test (p < 0.05). The p-values for each category of the MR findings according to the different groups of the KT-2000 measurements were 0.9180 for the MR signal intensity, 1.0000 for sharpness, 0.5038 for straightness and 0.2950 for thickness of the ACL. The MR findings were not significantly different between the different KT-2000 groups. MR imaging itself is not a reliable examination to predict stability of the ACL rupture outcome, even when the MR images show an intact appearance of the ACL.

  7. Stereochemical criteria for prediction of the effects of proline mutations on protein stability.

    Directory of Open Access Journals (Sweden)

    Kanika Bajaj

    2007-12-01

    Full Text Available When incorporated into a polypeptide chain, proline (Pro differs from all other naturally occurring amino acid residues in two important respects. The phi dihedral angle of Pro is constrained to values close to -65 degrees and Pro lacks an amide hydrogen. Consequently, mutations which result in introduction of Pro can significantly affect protein stability. In the present work, we describe a procedure to accurately predict the effect of Pro introduction on protein thermodynamic stability. Seventy-seven of the 97 non-Pro amino acid residues in the model protein, CcdB, were individually mutated to Pro, and the in vivo activity of each mutant was characterized. A decision tree to classify the mutation as perturbing or nonperturbing was created by correlating stereochemical properties of mutants to activity data. The stereochemical properties including main chain dihedral angle phi and main chain amide H-bonds (hydrogen bonds were determined from 3D models of the mutant proteins built using MODELLER. We assessed the performance of the decision tree on a large dataset of 163 single-site Pro mutations of T4 lysozyme, 74 nsSNPs, and 52 other Pro substitutions from the literature. The overall accuracy of this algorithm was found to be 81% in the case of CcdB, 77% in the case of lysozyme, 76% in the case of nsSNPs, and 71% in the case of other Pro substitution data. The accuracy of Pro scanning mutagenesis for secondary structure assignment was also assessed and found to be at best 69%. Our prediction procedure will be useful in annotating uncharacterized nsSNPs of disease-associated proteins and for protein engineering and design.

  8. Stability of gene expression and epigenetic profiles highlights the utility of patient-derived paediatric acute lymphoblastic leukaemia xenografts for investigating molecular mechanisms of drug resistance.

    Science.gov (United States)

    Wong, Nicholas C; Bhadri, Vivek A; Maksimovic, Jovana; Parkinson-Bates, Mandy; Ng, Jane; Craig, Jeff M; Saffery, Richard; Lock, Richard B

    2014-06-01

    Patient-derived tumour xenografts are an attractive model for preclinical testing of anti-cancer drugs. Insights into tumour biology and biomarkers predictive of responses to chemotherapeutic drugs can also be gained from investigating xenograft models. As a first step towards examining the equivalence of epigenetic profiles between xenografts and primary tumours in paediatric leukaemia, we performed genome-scale DNA methylation and gene expression profiling on a panel of 10 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) tumours that were stratified by prednisolone response. We found high correlations in DNA methylation and gene expression profiles between matching primary and xenograft tumour samples with Pearson's correlation coefficients ranging between 0.85 and 0.98. In order to demonstrate the potential utility of epigenetic analyses in BCP-ALL xenografts, we identified DNA methylation biomarkers that correlated with prednisolone responsiveness of the original tumour samples. Differential methylation of CAPS2, ARHGAP21, ARX and HOXB6 were confirmed by locus specific analysis. We identified 20 genes showing an inverse relationship between DNA methylation and gene expression in association with prednisolone response. Pathway analysis of these genes implicated apoptosis, cell signalling and cell structure networks in prednisolone responsiveness. The findings of this study confirm the stability of epigenetic and gene expression profiles of paediatric BCP-ALL propagated in mouse xenograft models. Further, our preliminary investigation of prednisolone sensitivity highlights the utility of mouse xenograft models for preclinical development of novel drug regimens with parallel investigation of underlying gene expression and epigenetic responses associated with novel drug responses.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Madeline eHarms

    2014-04-01

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

  11. Predicting physical stability in pressurized metered dose inhalers via dwell and instantaneous force colloidal probe microscopy.

    Science.gov (United States)

    D'Sa, Dexter; Chan, Hak-Kim; Chrzanowski, Wojciech

    2014-09-01

    Colloidal probe microscopy (CPM) is a quantitative predictive tool, which can offer insight into particle behavior in suspension pressurized metered dose inhalers (pMDIs). Although CPM instantaneous force measurements, which involve immediate retraction of the probe upon sample contact, can provide information on inter-particle attractive forces, they lack the ability to appropriately imitate all critical particle pMDI interactions (e.g., particle re-dispersion after prolonged pMDI storage). In this paper, two novel dwell force techniques - indentation and deflection dwell - were employed to mimic long-term particle interactions present in pMDIs, using particles of various internal structures and a model liquid propellant (2H,3H perfluoropentane) as a model system. Dwell measurements involve particle contact for an extended period of time. In deflection dwell mode the probe is held at a specific position, while in indentation dwell mode the probe is forced into the sample with a constant force for the entirety of the contact time. To evaluate the applicability of CPM to predict actual pMDI physical stability, inter-particle force measurements were compared with qualitative and quantitative bulk pMDI measurement techniques (visual quality and light scattering). Measured instantaneous attractive (snap-in) and adhesive (max-pull) forces decreased as a function of increasing surface area, while adhesive forces measured by indentation dwell decreased as a function of dwell contact time for particles containing voids. Instantaneous force measurements provided information on the likelihood of floccule formation, which was predictive of partitioning rates, while indentation dwell force measurements were predictive of formulation re-dispersibility after prolonged storage. Dwell force measurements provide additional information on particle behavior within a pMDI not obtainable via instantaneous measurements. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Development of fuzzy logic system to predict the SAW weldment shape profiles

    Science.gov (United States)

    Narang, H. K.; Mahapatra, M. M.; Jha, P. K.; Biswas, P.

    2012-09-01

    A fuzzy model was presented to predict the weldment shape profile of submerged arc welds (SAW) including the shape of heat affected zone (HAZ). The SAW bead-on-plates were welded by following a full factorial design matrix. The design matrix consisted of three levels of input welding process parameters. The welds were cross-sectioned and etched, and the zones were measured. A mapping technique was used to measure the various segments of the weld zones. These mapped zones were used to build a fuzzy logic model. The membership functions of the fuzzy model were chosen for the accurate prediction of the weld zone. The fuzzy model was further tested for a set of test case data. The weld zone predicted by the fuzzy logic model was compared with the experimentally obtained shape profiles and close agreement between the two was noted. The mapping technique developed for the weld zones and the fuzzy logic model can be used for on-line control of the SAW process. From the SAW fuzzy logic model an estimation of the fusion and HAZ can also be developed.

  13. Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

    Science.gov (United States)

    Enroth, Stefan; Enroth, Sofia Bosdotter; Johansson, Åsa; Gyllensten, Ulf

    2015-12-01

    Ageing is linked to a number of changes in how the body and its organs function. On a molecular level, ageing is associated with a reduction of telomere length, changes in metabolic and gene-transcription profiles and an altered DNA-methylation pattern. Lifestyle factors such as smoking or stress can impact some of these molecular processes and thereby affect the ageing of an individual. Here we demonstrate by analysis of 77 plasma proteins in 976 individuals, that the abundance of circulating proteins accurately predicts chronological age, as well as anthropometrical measurements such as weight, height and hip circumference. The plasma protein profile can also be used to identify lifestyle factors that accelerate and decelerate ageing. We found smoking, high BMI and consumption of sugar-sweetened beverages to increase the predicted chronological age by 2-6 years, while consumption of fatty fish, drinking moderate amounts of coffee and exercising reduced the predicted age by approximately the same amount. This method can be applied to dried blood spots and may thus be useful in forensic medicine to provide basic anthropometrical measures for an individual based on a biological evidence sample.

  14. Optimal first trimester preeclampsia prediction: a comparison of multimarker algorithm, risk profiles and their sequential application.

    Science.gov (United States)

    Gabbay-Benziv, R; Oliveira, N; Baschat, A A

    2016-01-01

    To compare performance of multimarker algorithm, risk profiles and their sequential application in prediction of preeclampsia and determining potential intervention targets. Maternal characteristics, ultrasound variables and serum biomarkers were collected prospectively at first trimester. Univariate analysis identified preeclampsia associated variables followed by logistic regression analysis to determine the prediction rule. Combined characteristics of the cardiovascular, metabolic and the personal risk factors were compared to the multimarker algorithm and the sequential application of both methods. Out of 2433 women, 108 developed preeclampsia (4.4%). Probability scores considering nulliparity, prior preeclampsia, body mass index, diastolic blood pressure and placental growth factor had an area under the receiver operating characteristic curve 0.784 (95% CI = 0.721-0.847). While the multimarker algorithm had the lowest false negative rate, sequential application of cardiovascular and metabolic risk profiles in screen positives reduced false positives by 26% and identified blood pressure and metabolic risk in 49/54 (91%) women with subsequent preeclampsia as treatable risk factors. Sequential application of a multimarker algorithm followed by determination of treatable risk factors in screen positive women is the optimal approach for first trimester preeclampsia prediction and identification of women that may benefit from targeted metabolic or cardiovascular treatment. © 2015 John Wiley & Sons, Ltd. © 2015 John Wiley & Sons, Ltd.

  15. Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

    Directory of Open Access Journals (Sweden)

    Joseph J Babcock

    Full Text Available Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

  16. Cytokine Profiles during Invasive Nontyphoidal Salmonella Disease Predict Outcome in African Children

    Science.gov (United States)

    Gilchrist, James J.; Heath, Jennifer N.; Msefula, Chisomo L.; Gondwe, Esther N.; Naranbhai, Vivek; Mandala, Wilson; MacLennan, Jenny M.; Molyneux, Elizabeth M.; Graham, Stephen M.; Drayson, Mark T.; Molyneux, Malcolm E.

    2016-01-01

    Nontyphoidal Salmonella is a leading cause of sepsis in African children. Cytokine responses are central to the pathophysiology of sepsis and predict sepsis outcome in other settings. In this study, we investigated cytokine responses to invasive nontyphoidal Salmonella (iNTS) disease in Malawian children. We determined serum concentrations of 48 cytokines with multiplexed immunoassays in Malawian children during acute iNTS disease (n = 111) and in convalescence (n = 77). Principal component analysis and logistic regression were used to identify cytokine signatures of acute iNTS disease. We further investigated whether these responses are altered by HIV coinfection or severe malnutrition and whether cytokine responses predict inpatient mortality. Cytokine changes in acute iNTS disease were associated with two distinct cytokine signatures. The first is characterized by increased concentrations of mediators known to be associated with macrophage function, and the second is characterized by raised pro- and anti-inflammatory cytokines typical of responses reported in sepsis secondary to diverse pathogens. These cytokine responses were largely unaltered by either severe malnutrition or HIV coinfection. Children with fatal disease had a distinctive cytokine profile, characterized by raised mediators known to be associated with neutrophil function. In conclusion, cytokine responses to acute iNTS infection in Malawian children are reflective of both the cytokine storm typical of sepsis secondary to diverse pathogens and the intramacrophage replicative niche of NTS. The cytokine profile predictive of fatal disease supports a key role of neutrophils in the pathogenesis of NTS sepsis. PMID:27170644

  17. Response-predictive gene expression profiling of glioma progenitor cells in vitro.

    Directory of Open Access Journals (Sweden)

    Sylvia Moeckel

    Full Text Available High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist.In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a to enrich specimens for brain tumor initiating cells and (b to confront cells with a therapeutic agent before expression profiling.As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro.For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

  18. Cardiovascular regulation profile predicts developmental trajectory of BMI and pediatric obesity.

    Science.gov (United States)

    Graziano, Paulo A; Calkins, Susan D; Keane, Susan P; O'Brien, Marion

    2011-09-01

    The present study examined the role of cardiovascular regulation in predicting pediatric obesity. Participants for this study included 268 children (141 girls) obtained from a larger ongoing longitudinal study. To assess cardiac vagal regulation, resting measures of respiratory sinus arrhythmia (RSA) and RSA change (vagal withdrawal) to three cognitively challenging tasks were derived when children were 5.5 years of age. Heart period (HP) and HP change (heart rate (HR) acceleration) were also examined. Height and weight measures were collected when children were 5.5, 7.5, and 10.5 years of age. Results indicated that physiological regulation at age 5.5 was predictive of both normal variations in BMI development and pediatric obesity at age 10.5. Specifically, children with a cardiovascular regulation profile characterized by lower levels of RSA suppression and HP change experienced significantly greater levels of BMI growth and were more likely to be classified as overweight/at-risk for overweight at age 10.5 compared to children with a cardiovascular regulation profile characterized by high levels of RSA suppression and HP change. However, a significant interaction with racial status was found suggesting that the association between cardiovascular regulation profile and BMI growth and pediatric obesity was only significant for African-American children. An autonomic cardiovascular regulation profile consisting of low parasympathetic activity represents a significant individual risk factor for the development of pediatric obesity, but only for African-American children. Mechanisms by which early physiological regulation difficulties may contribute to the development of pediatric obesity are discussed.

  19. Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.

    Science.gov (United States)

    Yousefi, Safoora; Amrollahi, Fatemeh; Amgad, Mohamed; Dong, Chengliang; Lewis, Joshua E; Song, Congzheng; Gutman, David A; Halani, Sameer H; Velazquez Vega, Jose Enrique; Brat, Daniel J; Cooper, Lee A D

    2017-09-15

    Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. Many prediction methods face limitations in learning from the high-dimensional profiles generated by these platforms, and rely on experts to hand-select a small number of features for training prediction models. In this paper, we demonstrate how deep learning and Bayesian optimization methods that have been remarkably successful in general high-dimensional prediction tasks can be adapted to the problem of predicting cancer outcomes. We perform an extensive comparison of Bayesian optimized deep survival models and other state of the art machine learning methods for survival analysis, and describe a framework for interpreting deep survival models using a risk backpropagation technique. Finally, we illustrate that deep survival models can successfully transfer information across diseases to improve prognostic accuracy. We provide an open-source software implementation of this framework called SurvivalNet that enables automatic training, evaluation and interpretation of deep survival models.

  20. Prediction and measurement of the depletion interaction in charged colloidal systems and its effect on stability

    Science.gov (United States)

    Sharma, Amber

    This dissertation was a study of the effect of introducing a nonadsorbing polyelectrolyte to a colloidal dispersion. Nonadsorbing macromolecular species in a colloidal dispersion result in what is termed the depletion effect. These macromolecules can be polymer molecules, micelles or other aggregates, or even other small particles. As two colloidal particles approach each other, such as through Brownian motion, the concentration of macromolecules in the gap region is altered relative to the bulk. At small separations, the macromolecules are excluded from the gap region, producing a depletion layer. This reduced concentration results in a lower osmotic pressure relative to the bulk and the resulting attraction is termed the depletion force. A force-balance model was developed to calculate the interaction force between two spherical particles in the presence of nonadsorbing spherical macromolecules. Both the higher order effects resulting from interactions between the macromolecules and, long range electrostatic repulsion for the macromolecule-macromolecule and particle-macromolecule interaction were included. The depletion interaction energy between a charged colloidal sphere and a charged flat plate in the presence of nonadsorbing silica macromolecules was measured using the optical technique of total internal reflection microscopy (TIRM). Comparisons of the measured energies to those predicted using a force-balance model indicated that the silica particles contribute slightly to the screening of the electrostatic interaction between the polystyrene particle and plate. Adjustment for this screening produces good agreement between theory and experiment. The effect of nonadsorbing silica on the stability of an electrically-stabilized dispersion of polystyrene latex was monitored using optical light scattering. Because of long range attractive depletion forces, reversible secondary flocculation of the particles occurred into a local potential energy minima. As has

  1. Development and Application of Predictive Tools for MHD Stability Limits in Tokamaks

    Energy Technology Data Exchange (ETDEWEB)

    Brennan, Dylan [Princeton Univ., NJ (United States); Miller, G. P. [Univ. of Tulsa, Tulsa, AZ (United States)

    2016-10-03

    This is a project to develop and apply analytic and computational tools to answer physics questions relevant to the onset of non-ideal magnetohydrodynamic (MHD) instabilities in toroidal magnetic confinement plasmas. The focused goal of the research is to develop predictive tools for these instabilities, including an inner layer solution algorithm, a resistive wall with control coils, and energetic particle effects. The production phase compares studies of instabilities in such systems using analytic techniques, PEST- III and NIMROD. Two important physics puzzles are targeted as guiding thrusts for the analyses. The first is to form an accurate description of the physics determining whether the resistive wall mode or a tearing mode will appear first as β is increased at low rotation and low error fields in DIII-D. The second is to understand the physical mechanism behind recent NIMROD results indicating strong damping and stabilization from energetic particle effects on linear resistive modes. The work seeks to develop a highly relevant predictive tool for ITER, advance the theoretical description of this physics in general, and analyze these instabilities in experiments such as ASDEX Upgrade, DIII-D, JET, JT-60U and NTSX. The awardee on this grant is the University of Tulsa. The research efforts are supervised principally by Dr. Brennan. Support is included for two graduate students, and a strong collaboration with Dr. John M. Finn of LANL. The work includes several ongoing collaborations with General Atomics, PPPL, and the NIMROD team, among others.

  2. Stabilizing Effects for Antibody Formulations and Safety Profiles of Cyclodextrin Polypseudorotaxane Hydrogels.

    Science.gov (United States)

    Higashi, Taishi; Ohshita, Naoko; Hirotsu, Tatsunori; Yamashita, Yoshihito; Motoyama, Keiichi; Koyama, Sawako; Iibuchi, Ruriko; Uchida, Takayuki; Mieda, Shiuhei; Handa, Kenji; Kimoto, Tomoaki; Arima, Hidetoshi

    2017-05-01

    Antibodies often have poor physicochemical stability during storage and transport, which is a serious drawback for the development of antibody-based drugs. In this study, we prepared polypseudorotaxane (PPRX) hydrogels consisting of cyclodextrins (CyDs) and polyethylene glycol, and evaluated them as stabilizers for commercially available antibody-based drugs. α-CyD and γ-CyD formed PPRX hydrogels with polyethylene glycol (molecular weight 20,000 Da) in the presence of antibody-based drugs such as omalizumab, palivizumab, panitumumab, and ranibizumab. Importantly, both α- and γ-CyD PPRX hydrogel formulations provided high stabilizing effects (ca. 100%) to the all antibody-based drugs used in this study. Furthermore, approximately 100% of the binding activity of omalizumab to the immunoglobulin E receptor was retained after the release from the hydrogels. Plasma levels of omalizumab after subcutaneous injection of the γ-CyD PPRX hydrogel to rats were equivalent to those of omalizumab alone. According to the results of blood chemistry tests, the weights of organs and histological observations α- and γ-CyD PPRX hydrogels induced no serious adverse effects. These results suggest that CyD PPRX hydrogels are useful as safe and promising stabilizing formulations for antibody-based drugs. Copyright © 2017. Published by Elsevier Inc.

  3. Effect of processing methods on the stability and nutritional profiles of navy bean-soybean emulsions

    Science.gov (United States)

    In this study, an innovative emulsion made from soybean and navy bean blends of different proportionalities was developed. In addition, two processing methods were evaluated: traditional cooking and jet-cooking. The physical attributes and storage stability were measured and compared. This study fou...

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

    Science.gov (United States)

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

    2017-07-24

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

  5. Stability and Heterogeneity of Expression Profiles in Lung Cancer Specimens Harvested Following Surgical Resection

    Directory of Open Access Journals (Sweden)

    Fiona H. Blackhall

    2004-11-01

    Full Text Available One of the major concerns in microarray profiling studies of clinical samples is the effect of tissue sampling and RNA extraction on data. We analyzed gene expression in lung cancer specimens that were serially harvested from tumor mass and snap-frozen at several intervals up to 120 minutes after surgical resection. Global gene expression was profiled on cDNA microarrays, and selected stress and hypoxia-activated genes were evaluated using real-time reverse transcription polymerase chain reaction (RT-PCR. Remarkably, similar gene expression profiles were obtained for the majority of samples regardless of the time that had elapsed between resection and freezing. Real-time RT-PCR studies showed significant heterogeneity in the expression levels of stress and hypoxia-activated genes in samples obtained from different areas of a tumor specimen at one time point after resection. The variations between multiple samplings were significantly greater than those of elapsed time between sampling/freezing. Overall samples snap-frozen within 30 to 60 minutes of surgical resection are acceptable for gene expression studies, thus making sampling and snap-freezing of tumor samples in a routine surgical pathology laboratory setting feasible. However, sampling and pooling from multiple sites of each tumor may be necessary for expression profiling studies to overcome the molecular heterogeneity present in tumor specimens.

  6. Stability and change of lifestyle profiles in cardiovascular patients after their first acute coronary event.

    Directory of Open Access Journals (Sweden)

    Patrizia Steca

    Full Text Available Acute coronary syndrome (ACS is a major cause of morbidity and mortality. Lifestyle and health behavior changes play an important role in the primary and secondary prevention of ACS recurrence. Changes in unhealthy lifestyles after an acute coronary event have been analyzed by considering separate behaviors individually, even though research on the healthy population has demonstrated that unhealthy behaviors tend to co-occur.The aim of this study was to identify lifestyle profiles of ACS patients and to explore their pathways of change for one year after their first coronary event by adopting a typological approach.Two hundred and twenty-three patients (84% male; mean age = 57.14 completed self-report measures of health-related behaviors at the beginning of cardiac rehabilitation, and six months and twelve months after. At each wave depression, anxiety and heart rate were also evaluated. Cluster analysis was performed to identify lifestyle profiles and to analyze their change over time. Differences in psychological factors and heart rate among clusters were assessed.Patients' diet, physical activity, and smoking behavior greatly improved six months after their first coronary event. No further improvements were detected after one year. At each wave specific lifestyle profiles were identified, ranging from more maladaptive to healthier clusters. Patients with multiple unhealthy behaviors experience greater difficulties in maintaining a healthier lifestyle over time. Moreover, the results demonstrated the association between lifestyle profiles at twelve months after the acute coronary event and depression measured six months earlier. Finally, the most maladaptive lifestyle profile had many members with elevated heart rate at twelve months after the cardiac rehabilitation.Current findings may have a strong practical impact in the development and implementation of personalized secondary prevention programs targeting lifestyles of ACS patients.

  7. Extending the predictions of chemical mechanisms for hydrogen combustion by Comparison of predicted and measured flame temperatures in burner-stabilized, 1-D flames

    NARCIS (Netherlands)

    Sepman, A. V.; Mokhov, A. V.; Levinsky, H. B.

    A method is presented for extending the range of conditions for which the performance of chemical mechanisms used to predict hydrogen burning velocities can be evaluated. Specifically, by comparing the computed variation of flame temperature with mass flux in burner-stabilized flat flames with those

  8. Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV

    Directory of Open Access Journals (Sweden)

    Izaskun Garrido

    2016-08-01

    Full Text Available Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV. The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.

  9. Profiles of Dispositional Expectancies and Affectivity Predict Later Psychosocial Functioning in Children and Adolescents With Cancer.

    Science.gov (United States)

    Okado, Yuko; Howard Sharp, Katianne M; Tillery, Rachel; Long, Alanna M; Phipps, Sean

    2016-04-01

    Examined how individual differences in disposition among pediatric cancer patients predict their later psychosocial functioning. Patients aged 8-17 years (N = 223) reported on their disposition at baseline. One and three years later, self-reports and parent reports of patient psychosocial functioning were obtained. Latent profile analysis was used to identify subgroups that differed on baseline disposition and to compare them on later outcomes. Three groups were identified: The "Positive" group (59%) had high optimism and positive affectivity and low pessimism and negative affectivity; the "Moderate" group (39%) had a similar profile, with less exaggerated scores; a small, "Negative" group (2%) had the opposite profile (low optimism/positive affectivity; high pessimism/negative affectivity). These groups differed in psychosocial functioning at follow-up, generally in expected directions. Most patients have a disposition that may be protective. A small minority at high risk for maladjustment is distinguished by their disposition. © The Author 2015. 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.

  10. Prediction of mitochondrial protein function by comparative physiology and phylogenetic profiling.

    Science.gov (United States)

    Cheng, Yiming; Perocchi, Fabiana

    2015-01-01

    According to the endosymbiotic theory, mitochondria originate from a free-living alpha-proteobacteria that established an intracellular symbiosis with the ancestor of present-day eukaryotic cells. During the bacterium-to-organelle transformation, the proto-mitochondrial proteome has undergone a massive turnover, whereby less than 20 % of modern mitochondrial proteomes can be traced back to the bacterial ancestor. Moreover, mitochondrial proteomes from several eukaryotic organisms, for example, yeast and human, show a rather modest overlap, reflecting differences in mitochondrial physiology. Those differences may result from the combination of differential gain and loss of genes and retargeting processes among lineages. Therefore, an evolutionary signature, also called "phylogenetic profile", could be generated for every mitochondrial protein. Here, we present two evolutionary biology approaches to study mitochondrial physiology: the first strategy, which we refer to as "comparative physiology," allows the de novo identification of mitochondrial proteins involved in a physiological function; the second, known as "phylogenetic profiling," allows to predict protein functions and functional interactions by comparing phylogenetic profiles of uncharacterized and known components.

  11. Multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure.

    Directory of Open Access Journals (Sweden)

    Gilles Lemesle

    Full Text Available Risk stratification of patients with systolic chronic heart failure (HF is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%: 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 - 0.68 were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients.

  12. Multiple intravenous doses of paracetamol result in a predictable pharmacokinetic profile in very preterm infants.

    Science.gov (United States)

    van Ganzewinkel, C; Derijks, L; Anand, K J S; van Lingen, R A; Neef, C; Kramer, B W; Andriessen, P

    2014-06-01

    The therapeutic options available to treat neonatal pain are limited, and one alternative for nonopioid systemic treatment is paracetamol. However, pharmacokinetic data from prolonged administration of intravenous paracetamol in neonates are limited. The aim of this study was to present pharmacokinetics after multiple dose of intravenous paracetamol in very preterm infants of paracetamol (7.5 mg/kg). Blood samples were taken to measure paracetamol, glutathione and hepatic function, together with urine samples for paracetamol metabolites. A two-compartment pharmacokinetic model gave the best fit for all individual patients and resulted in a predictable pharmacokinetic profile. The estimated pharmacokinetic population parameters were volume of distribution 0.764 ± 0.225 L/kg, elimination rate constant (ke ) 0.117 ± 0.091/h and intercompartment rate constants k12 0.607 ± 0.734/h and k21 1.105 ± 0.762/h. Our study found that multiple doses of intravenous paracetamol resulted in a predictable pharmacokinetic profile in very preterm infants. Increases in postmenstrual age and weight were associated with increased clearance. No evidence of hepatotoxicity was found. ©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

  13. How good are publicly available web services that predict bioactivity profiles for drug repurposing?

    Science.gov (United States)

    Murtazalieva, K A; Druzhilovskiy, D S; Goel, R K; Sastry, G N; Poroikov, V V

    2017-10-01

    Drug repurposing provides a non-laborious and less expensive way for finding new human medicines. Computational assessment of bioactivity profiles shed light on the hidden pharmacological potential of the launched drugs. Currently, several freely available computational tools are available via the Internet, which predict multitarget profiles of drug-like compounds. They are based on chemical similarity assessment (ChemProt, SuperPred, SEA, SwissTargetPrediction and TargetHunter) or machine learning methods (ChemProt and PASS). To compare their performance, this study has created two evaluation sets, consisting of (1) 50 well-known repositioned drugs and (2) 12 drugs recently patented for new indications. In the first set, sensitivity values varied from 0.64 (TarPred) to 1.00 (PASS Online) for the initial indications and from 0.64 (TarPred) to 0.98 (PASS Online) for the repurposed indications. In the second set, sensitivity values varied from 0.08 (SuperPred) to 1.00 (PASS Online) for the initial indications and from 0.00 (SuperPred) to 1.00 (PASS Online) for the repurposed indications. Thus, this analysis demonstrated that the performance of machine learning methods surpassed those of chemical similarity assessments, particularly in the case of novel repurposed indications.

  14. Enniatin and Beauvericin Biosynthesis in Fusarium Species: Production Profiles and Structural Determinant Prediction

    Directory of Open Access Journals (Sweden)

    Vania C. Liuzzi

    2017-01-01

    Full Text Available Members of the fungal genus Fusarium can produce numerous secondary metabolites, including the nonribosomal mycotoxins beauvericin (BEA and enniatins (ENNs. Both mycotoxins are synthesized by the multifunctional enzyme enniatin synthetase (ESYN1 that contains both peptide synthetase and S-adenosyl-l-methionine-dependent N-methyltransferase activities. Several Fusarium species can produce ENNs, BEA or both, but the mechanism(s enabling these differential metabolic profiles is unknown. In this study, we analyzed the primary structure of ESYN1 by sequencing esyn1 transcripts from different Fusarium species. We measured ENNs and BEA production by ultra-performance liquid chromatography coupled with photodiode array and Acquity QDa mass detector (UPLC-PDA-QDa analyses. We predicted protein structures, compared the predictions by multivariate analysis methods and found a striking correlation between BEA/ENN-producing profiles and ESYN1 three-dimensional structures. Structural differences in the β strand’s Asn789-Ala793 and His797-Asp802 portions of the amino acid adenylation domain can be used to distinguish BEA/ENN-producing Fusarium isolates from those that produce only ENN.

  15. The potential use of expression profiling: implications for predicting treatment response in rheumatoid arthritis.

    Science.gov (United States)

    Smith, Samantha Louise; Plant, Darren; Eyre, Stephen; Barton, Anne

    2013-07-01

    Whole genome expression profiling, or transcriptomics, is a high throughput technology with the potential for major impacts in both clinical settings and drug discovery and diagnostics. In particular, there is much interest in this technique as a mechanism for predicting treatment response. Gene expression profiling entails the quantitative measurement of messenger RNA levels for thousands of genes simultaneously with the inherent possibility of identifying biomarkers of response to a particular therapy or by singling out those at risk of serious adverse events. This technology should contribute to the era of stratified medicine, in which patient specific populations are matched to potentially beneficial drugs via clinical tests. Indeed, in the oncology field, gene expression testing is already recommended to allow rational use of therapies to treat breast cancer. However, there are still many issues surrounding the use of the various testing platforms available and the statistical analysis associated with the interpretation of results generated. This review will discuss the implications this promising technology has in predicting treatment response and outline the various advantages and pitfalls associated with its use.

  16. Profiles of verbal working memory growth predict speech and language development in children with cochlear implants.

    Science.gov (United States)

    Kronenberger, William G; Pisoni, David B; Harris, Michael S; Hoen, Helena M; Xu, Huiping; Miyamoto, Richard T

    2013-06-01

    Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of development of verbal STM/WM and speech-language skills. In this study, the authors investigated relations between profiles of verbal STM/WM development and speech-language development over time. Profiles of verbal STM/WM development were identified through the use of group-based trajectory analysis of repeated digit span measures over at least a 2-year time period in a sample of 66 children (ages 6-16 years) with CIs. Subjects also completed repeated assessments of speech and language skills during the same time period. Clusters representing different patterns of development of verbal STM (digit span forward scores) were related to the growth rate of vocabulary and language comprehension skills over time. Clusters representing different patterns of development of verbal WM (digit span backward scores) were related to the growth rate of vocabulary and spoken word recognition skills over time. Different patterns of development of verbal STM/WM capacity predict the dynamic process of development of speech and language skills in this clinical population.

  17. CDK4 phosphorylation status and a linked gene expression profile predict sensitivity to palbociclib.

    Science.gov (United States)

    Raspé, Eric; Coulonval, Katia; Pita, Jaime M; Paternot, Sabine; Rothé, Françoise; Twyffels, Laure; Brohée, Sylvain; Craciun, Ligia; Larsimont, Denis; Kruys, Véronique; Sandras, Flavienne; Salmon, Isabelle; Van Laere, Steven; Piccart, Martine; Ignatiadis, Michail; Sotiriou, Christos; Roger, Pierre P

    2017-08-01

    Cyclin D-CDK4/6 are the first CDK complexes to be activated in the G1 phase in response to oncogenic pathways. The specific CDK4/6 inhibitor PD0332991 (palbociclib) was recently approved by the FDA and EMA for treatment of advanced ER-positive breast tumors. Unfortunately, no reliable predictive tools are available for identifying potentially responsive or insensitive tumors. We had shown that the activating T172 phosphorylation of CDK4 is the central rate-limiting event that initiates the cell cycle decision and signals the presence of active CDK4. Here, we report that the profile of post-translational modification including T172 phosphorylation of CDK4 differs among breast tumors and associates with their subtypes and risk. A gene expression signature faithfully predicted CDK4 modification profiles in tumors and cell lines. Moreover, in breast cancer cell lines, the CDK4 T172 phosphorylation best correlated with sensitivity to PD0332991. This gene expression signature identifies tumors that are unlikely to respond to CDK4/6 inhibitors and could help to select a subset of patients with HER2-positive and basal-like tumors for clinical studies on this class of drugs. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  18. Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles.

    Science.gov (United States)

    Khovanova, N A; Khovanov, I A; Sbano, L; Griffiths, F; Holt, T A

    2013-06-01

    Continuous glucose monitoring is increasingly used in the management of diabetes. Subcutaneous glucose profiles are characterised by a strong non-stationarity, which limits the application of correlation-spectral analysis. We derived an index of linear predictability by calculating the autocorrelation function of time series increments and applied detrended fluctuation analysis to assess the non-stationarity of the profiles. Time series from volunteers with both type 1 and type 2 diabetes and from control subjects were analysed. The results suggest that in control subjects, blood glucose variation is relatively uncorrelated, and this variation could be modelled as a random walk with no retention of 'memory' of previous values. In diabetes, variation is both greater and smoother, with retention of inter-dependence between neighbouring values. Essential components for adequate longer term prediction were identified via a decomposition of time series into a slow trend and responses to external stimuli. Implications for diabetes management are discussed. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  19. Anthropometric profile of elite acrobatic gymnasts and prediction of role performance.

    Science.gov (United States)

    Taboada-Iglesias, Yaiza; Gutiérrez-Sánchez, Águeda; Vernetta Santana, Mercedes

    2016-04-01

    This study is aimed at determining the anthropometric profile of acrobatic gymnasts, differentiating on the basis of their role. The sample consisted of 150 gymnasts (129 women and 21 men) from throughout Spain. The anthropometric measurements were taken according to the International Society for the Advancement of Kinanthropometry (ISAK) procedures. Morphological measurements, proportionality and somatotype were analyzed in both groups. A comparative analysis between groups and a prediction model were used to analyze the specific profile of each role. All morphological measurements showed significant differences (Pendomorphic element of the bases presented higher values than the tops, for whom the ectomorphy scores were higher. Bases have an endo-mesomorphic somatotype and tops present a balanced mesomorphic. There are no mesomorphy differences between the tops and bases. BMI was significantly higher in the bases (BMI=20.28 kg/m2). Proportionality differences between roles are shown. Both roles present negatives values for almost all variables studied except for the trochlear condyle of the humerus, the bicondyle of the femur and the wrist bistyloid breadth in tops and the wrist bistyloid breadth, the upper arm relaxed girths and maximum calf in bases. The best prediction model included thigh girth as the best explanatory covariate of role performance. Here are differences between both roles, bases being gymnasts of larger size than tops. However, they present no differences in the muscular component, as it might be expected.

  20. Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

    Directory of Open Access Journals (Sweden)

    Andrew J Olaharski

    2009-07-01

    Full Text Available Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases, yielding a 113x290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT. Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity. This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing

  1. 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

  2. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

    Science.gov (United States)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

  3. Prediction of Clinical Outcome Using Gene Expression Profiling and Artificial Neural Networks for Patients with Neuroblastoma

    Science.gov (United States)

    Wei, Jun S.; Greer, Braden T.; Westermann, Frank; Steinberg, Seth M.; Son, Chang-Gue; Chen, Qing-Rong; Whiteford, Craig C.; Bilke, Sven; Krasnoselsky, Alexei L.; Cenacchi, Nicola; Catchpoole, Daniel; Berthold, Frank; Schwab, Manfred; Khan, Javed

    2005-01-01

    Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children’s Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains artificial neural networks to develop an accurate predictor of survival for each individual patient with neuroblastoma. Using principal component analysis we found that neuroblastoma tumors exhibited inherent prognostic specific gene expression profiles. Subsequent artificial neural network-based prognosis prediction using expression levels of all 37,920 good-quality clones achieved 88% accuracy. Moreover, using an artificial neural network-based gene minimization strategy in a separate analysis we identified 19 genes, including 2 prognostic markers reported previously, MYCN and CD44, which correctly predicted outcome for 98% of these patients. In addition, these 19 predictor genes were able to additionally partition Children’s Oncology Group-stratified high-risk patients into two subgroups according to their survival status (P = 0.0005). Our findings provide evidence of a gene expression signature that can predict prognosis independent of currently known risk factors and could assist physicians in the individual management of patients with high-risk neuroblastoma. PMID:15466177

  4. TEMA and Dot Enumeration Profiles Predict Mental Addition Problem Solving Speed Longitudinally

    Directory of Open Access Journals (Sweden)

    Clare S. Major

    2017-12-01

    Full Text Available Different math indices can be used to assess math potential at school entry. We evaluated whether standardized math achievement (TEMA-2 performance, core number abilities (dot enumeration, symbolic magnitude comparison, non-verbal intelligence (NVIQ and visuo-spatial working memory (VSWM, in combination or separately, predicted mental addition problem solving speed over time. We assessed 267 children’s TEMA-2, magnitude comparison, dot enumeration, and VSWM abilities at school entry (5 years and NVIQ at 8 years. Mental addition problem solving speed was assessed at 6, 8, and 10 years. Longitudinal path analysis supported a model in which dot enumeration performance ability profiles and previous mental addition speed predicted future mental addition speed on all occasions, supporting a componential account of math ability. Standardized math achievement and NVIQ predicted mental addition speed at specific time points, while VSWM and symbolic magnitude comparison did not contribute unique variance to the model. The implications of using standardized math achievement and dot enumeration ability to index math learning potential at school entry are discussed.

  5. Postural stability, clicker reaction time and bow draw force predict performance in elite recurve archery.

    Science.gov (United States)

    Spratford, Wayne; Campbell, Rhiannon

    2017-06-01

    Recurve archery is an Olympic sport that requires extreme precision, upper body strength and endurance. The purpose of this research was to quantify how postural stability variables both pre- and post-arrow release, draw force, flight time, arrow length and clicker reaction time, collectively, impacted on the performance or scoring outcomes in elite recurve archery athletes. Thirty-nine elite-level recurve archers (23 male and 16 female; mean age = 24.7 ± 7.3 years) from four different countries volunteered to participate in this study prior to competing at a World Cup event. An AMTI force platform (1000Hz) was used to obtain centre of pressure (COP) measurements 1s prior to arrow release and 0.5s post-arrow release. High-speed footage (200Hz) allowed for calculation of arrow flight time and score. Results identified clicker reaction time, draw force and maximum sway speed as the variables that best predicted shot performance. Specifically, reduced clicker reaction time, greater bow draw force and reduced postural sway speed post-arrow release were predictors of higher scoring shots. It is suggested that future research should focus on investigating shoulder muscle tremors at full draw in relation to clicker reaction time, and the effect of upper body strength interventions (specifically targeting the musculature around the shoulder girdle) on performance in recurve archers.

  6. Top-down modulation in human visual cortex predicts the stability of a perceptual illusion

    Science.gov (United States)

    Meindertsma, Thomas; Hillebrand, Arjan; van Dijk, Bob W.; Lamme, Victor A. F.; Donner, Tobias H.

    2014-01-01

    Conscious perception sometimes fluctuates strongly, even when the sensory input is constant. For example, in motion-induced blindness (MIB), a salient visual target surrounded by a moving pattern suddenly disappears from perception, only to reappear after some variable time. Whereas such changes of perception result from fluctuations of neural activity, mounting evidence suggests that the perceptual changes, in turn, may also cause modulations of activity in several brain areas, including visual cortex. In this study, we asked whether these latter modulations might affect the subsequent dynamics of perception. We used magnetoencephalography (MEG) to measure modulations in cortical population activity during MIB. We observed a transient, retinotopically widespread modulation of beta (12–30 Hz)-frequency power over visual cortex that was closely linked to the time of subjects' behavioral report of the target disappearance. This beta modulation was a top-down signal, decoupled from both the physical stimulus properties and the motor response but contingent on the behavioral relevance of the perceptual change. Critically, the modulation amplitude predicted the duration of the subsequent target disappearance. We propose that the transformation of the perceptual change into a report triggers a top-down mechanism that stabilizes the newly selected perceptual interpretation. PMID:25411458

  7. Plasma Lipidomic Profiling of Treated HIV-Positive Individuals and the Implications for Cardiovascular Risk Prediction

    Science.gov (United States)

    Wong, Gerard; Trevillyan, Janine M.; Fatou, Benoit; Cinel, Michelle; Weir, Jacquelyn M.; Hoy, Jennifer F.; Meikle, Peter J.

    2014-01-01

    Background The increased risk of coronary artery disease in human immunodeficiency virus (HIV) positive patients is collectively contributed to by the human immunodeficiency virus and antiretroviral-associated dyslipidaemia. In this study, we investigate the characterisation of the plasma lipid profiles of treated HIV patients and the relationship of 316 plasma lipid species across multiple lipid classes with the risk of future cardiovascular events in HIV- positive patients. Methods In a retrospective case-control study, we analysed plasma lipid profiles of 113 subjects. Cases (n = 23) were HIV-positive individuals with a stored blood sample available 12 months prior to their diagnosis of coronary artery disease (CAD). They were age and sex matched to HIV-positive individuals without a diagnosis of CAD (n = 45) and with healthy HIV-negative volunteers (n = 45). Results Association of plasma lipid species and classes with HIV infection and cardiovascular risk in HIV were determined. In multiple logistic regression, we identified 83 lipids species and 7 lipid classes significantly associated with HIV infection and a further identified 74 lipid species and 8 lipid classes significantly associated with future cardiovascular events in HIV-positive subjects. Risk prediction models incorporating lipid species attained an area under the receiver operator characteristic curve (AUC) of 0.78 (0.775, 0.785)) and outperformed all other tested markers and risk scores in the identification of HIV-positive subjects with increased risk of cardiovascular events. Conclusions Our results demonstrate that HIV-positive patients have significant differences in their plasma lipid profiles compared with healthy HIV-negative controls and that numerous lipid species were significantly associated with elevated cardiovascular risk. This suggests a potential novel application for plasma lipids in cardiovascular risk screening of HIV-positive patients. PMID:24733512

  8. Plasma lipidomic profiling of treated HIV-positive individuals and the implications for cardiovascular risk prediction.

    Directory of Open Access Journals (Sweden)

    Gerard Wong

    Full Text Available BACKGROUND: The increased risk of coronary artery disease in human immunodeficiency virus (HIV positive patients is collectively contributed to by the human immunodeficiency virus and antiretroviral-associated dyslipidaemia. In this study, we investigate the characterisation of the plasma lipid profiles of treated HIV patients and the relationship of 316 plasma lipid species across multiple lipid classes with the risk of future cardiovascular events in HIV-positive patients. METHODS: In a retrospective case-control study, we analysed plasma lipid profiles of 113 subjects. Cases (n = 23 were HIV-positive individuals with a stored blood sample available 12 months prior to their diagnosis of coronary artery disease (CAD. They were age and sex matched to HIV-positive individuals without a diagnosis of CAD (n = 45 and with healthy HIV-negative volunteers (n = 45. RESULTS: Association of plasma lipid species and classes with HIV infection and cardiovascular risk in HIV were determined. In multiple logistic regression, we identified 83 lipids species and 7 lipid classes significantly associated with HIV infection and a further identified 74 lipid species and 8 lipid classes significantly associated with future cardiovascular events in HIV-positive subjects. Risk prediction models incorporating lipid species attained an area under the receiver operator characteristic curve (AUC of 0.78 (0.775, 0.785 and outperformed all other tested markers and risk scores in the identification of HIV-positive subjects with increased risk of cardiovascular events. CONCLUSIONS: Our results demonstrate that HIV-positive patients have significant differences in their plasma lipid profiles compared with healthy HIV-negative controls and that numerous lipid species were significantly associated with elevated cardiovascular risk. This suggests a potential novel application for plasma lipids in cardiovascular risk screening of HIV-positive patients.

  9. Plasma lipidomic profiling of treated HIV-positive individuals and the implications for cardiovascular risk prediction.

    Science.gov (United States)

    Wong, Gerard; Trevillyan, Janine M; Fatou, Benoit; Cinel, Michelle; Weir, Jacquelyn M; Hoy, Jennifer F; Meikle, Peter J

    2014-01-01

    The increased risk of coronary artery disease in human immunodeficiency virus (HIV) positive patients is collectively contributed to by the human immunodeficiency virus and antiretroviral-associated dyslipidaemia. In this study, we investigate the characterisation of the plasma lipid profiles of treated HIV patients and the relationship of 316 plasma lipid species across multiple lipid classes with the risk of future cardiovascular events in HIV-positive patients. In a retrospective case-control study, we analysed plasma lipid profiles of 113 subjects. Cases (n = 23) were HIV-positive individuals with a stored blood sample available 12 months prior to their diagnosis of coronary artery disease (CAD). They were age and sex matched to HIV-positive individuals without a diagnosis of CAD (n = 45) and with healthy HIV-negative volunteers (n = 45). Association of plasma lipid species and classes with HIV infection and cardiovascular risk in HIV were determined. In multiple logistic regression, we identified 83 lipids species and 7 lipid classes significantly associated with HIV infection and a further identified 74 lipid species and 8 lipid classes significantly associated with future cardiovascular events in HIV-positive subjects. Risk prediction models incorporating lipid species attained an area under the receiver operator characteristic curve (AUC) of 0.78 (0.775, 0.785)) and outperformed all other tested markers and risk scores in the identification of HIV-positive subjects with increased risk of cardiovascular events. Our results demonstrate that HIV-positive patients have significant differences in their plasma lipid profiles compared with healthy HIV-negative controls and that numerous lipid species were significantly associated with elevated cardiovascular risk. This suggests a potential novel application for plasma lipids in cardiovascular risk screening of HIV-positive patients.

  10. Prediction of future risk of insulin resistance and metabolic syndrome based on Korean boy's metabolite profiling.

    Science.gov (United States)

    Lee, AeJin; Jang, Han Byul; Ra, Moonjin; Choi, Youngshim; Lee, Hye-Ja; Park, Ju Yeon; Kang, Jae Heon; Park, Kyung-Hee; Park, Sang Ick; Song, Jihyun

    2015-01-01

    Childhood obesity is strongly related to future insulin resistance and metabolic syndrome. Thus, identifying early biomarkers of obesity-related diseases based on metabolic profiling is useful to control future metabolic disorders. We compared metabolic profiles between obese and normal-weight children and investigated specific biomarkers of future insulin resistance and metabolic syndrome. In all, 186 plasma metabolites were analysed at baseline and after 2 years in 109 Korean boys (age 10.5±0.4 years) from the Korean Child Obesity Cohort Study using the AbsoluteIDQ™ p180 Kit. We observed that levels of 41 metabolites at baseline and 40 metabolites at follow-up were significantly altered in obese children (pObese children showed significantly higher levels of branched-chain amino acids (BCAAs) and several acylcarnitines and lower levels of acyl-alkyl phosphatidylcholines. Also, baseline BCAAs were significantly positively correlated with both homeostasis model assessment for insulin resistance (HOMA-IR) and continuous metabolic risk score at the 2-year follow-up. In logistic regression analyses with adjustments for degree of obesity at baseline, baseline BCAA concentration, greater than the median value, was identified as a predictor of future risk of insulin resistance and metabolic syndrome. High BCAA concentration could be "early" biomarkers for predicting future metabolic diseases. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

  11. Professional choice self-efficacy: predicting traits and personality profiles in high school students

    Directory of Open Access Journals (Sweden)

    Rodolfo Augusto Matteo Ambiel

    2016-01-01

    Full Text Available Abstract This study aimed to verify the predictive capacity of the Big Five personality factors related to professional choice self-efficacy, as well as to draw a personality profile of people with diverse self-efficacy levels. There were 308 high school students participating, from three different grades (57.5 % women, from public and private schools, average 26.64 years of age. Students completed two instruments, Escala de Autoeficácia para Escolha Profissional (Professional Choice Self-efficacy Scale and Bateria Fatorial de Personalidade (Factorial Personality Battery. Results were obtained using multiple regression analysis, analysis of variance with repeated measures profile and Cohen’s d to estimate the effect size of differences. Results showed that Extraversion, Agreeableness and Conscientiousness were the main predictors of self-efficacy. Differences from medium to large were observed between extreme groups, and Extraversion and Conscientiousness were the personality factors that better distinguish people with low and high levels of self-efficacy. Theses results partially corroborate with the hypothesis. Results were discussed based on literature and on the practical implications of the results. New studies are proposed.

  12. Stability and Change in Adjustment Profiles Among Chinese American Adolescents: The Role of Parenting.

    Science.gov (United States)

    Kim, Su Yeong; Wang, Yijie; Shen, Yishan; Hou, Yang

    2015-09-01

    Asian American adolescents are often depicted as academically successful but psychologically distressed, a pattern known as the achievement/adjustment paradox. In a sample of 444 Chinese American adolescents (54 % females), we identified three distinct patterns of adjustment in early adolescence, middle adolescence, and emerging adulthood: the well-adjusted group, which was the largest, exhibited high achievement and low psychological distress; the poorly-adjusted group exhibited poor achievement and moderate distress; and the paradox group exhibited relatively high achievement and high distress. More than half of the adolescents remained in the same profile over time. Adolescents with supportive parents were more likely to stay well-adjusted, and those with "tiger" parents were more likely to stay in the paradox group over time. The present study focused on the critical role of parenting in early adolescence, highlighting variations in Chinese American adolescents' adjustment in multiple domains over time.

  13. The effects of flute shape and thread profile on the insertion torque and primary stability of dental implants.

    Science.gov (United States)

    Wu, Shu-Wei; Lee, Chia-Ching; Fu, Ping-Yuen; Lin, Shang-Chih

    2012-09-01

    Easy insertion of the implant and stable bone purchase is essential for an ideal dental implantation. At the implant tip, the cutting flutes and conical profile are respectively designed to reduce insertion resistance and facilitate the initial insertion. However, the tapered tip might reduce the self-tapping and bone-purchasing abilities of the flutes and the tip threads. Using sawbone blocks as standard specimens, this study experimentally measures the insertion torque, holding power, and bending strength of eight varieties of implant (4 shapes×2 profiles). The bony contact, interfacial mechanism, and the altered shape of the flutes, at different section planes, are used to explain the experimental results. The results reveal that the bone-implant gaps at the tip region significantly suppress both the self-tapping and bone-purchasing abilities of the flutes and the tip threads. This makes initial insertion of the conical implant easier. However, the conical implant eventually requires a higher insertion torque and holding power, due to tighter bony contact, at the tail threads. The bowl-fluted design has the least flute space to store the squeezed bone chips, so both insertion torque and bending strength are significantly higher. For the conical group, the holding powers of three flute designs are nearly comparable. Overall, the conical implant with bowl flutes is the optimal design, with a lower resistance to initial insertion and higher stability, for final instrumentation. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

  14. Transcriptional Profiling Confirms the Therapeutic Effects of Mast Cell Stabilization in a Dengue Disease Model.

    Science.gov (United States)

    Morrison, Juliet; Rathore, Abhay P S; Mantri, Chinmay K; Aman, Siti A B; Nishida, Andrew; St John, Ashley L

    2017-09-15

    There are no approved therapeutics for the treatment of dengue disease despite the global prevalence of dengue virus (DENV) and its mosquito vectors. DENV infections can lead to vascular complications, hemorrhage, and shock due to the ability of DENV to infect a variety of immune and nonimmune cell populations. Increasingly, studies have implicated the host response as a major contributor to severe disease. Inflammatory products of various cell types, including responding T cells, mast cells (MCs), and infected monocytes, can contribute to immune pathology. In this study, we show that the host response to DENV infection in immunocompetent mice recapitulates transcriptional changes that have been described in human studies. We found that DENV infection strongly induced metabolic dysregulation, complement signaling, and inflammation. DENV also affected the immune cell content of the spleen and liver, enhancing NK, NKT, and CD8 + T cell activation. The MC-stabilizing drug ketotifen reversed many of these responses without suppressing memory T cell formation and induced additional changes in the transcriptome and immune cell composition of the spleen, consistent with reduced inflammation. This study provides a global transcriptional map of immune activation in DENV target organs of an immunocompetent host and supports the further development of targeted immunomodulatory strategies to treat DENV disease. IMPORTANCE Dengue virus (DENV), which causes febrile illness, is transmitted by mosquito vectors throughout tropical and subtropical regions of the world. Symptoms of DENV infection involve damage to blood vessels and, in rare cases, hemorrhage and shock. Currently, there are no targeted therapies to treat DENV infection, but it is thought that drugs that target the host immune response may be effective in limiting symptoms that result from excessive inflammation. In this study, we measured the host transcriptional response to infection in multiple DENV target organs

  15. The Fuzzy Logic Model for the Prediction of Marshall Stability of Lightweight Asphalt Concretes Fabricated using Expanded Clay Aggregate

    Directory of Open Access Journals (Sweden)

    Sercan SERİN

    2014-07-01

    Full Text Available In the study, predictability of Marshall Stability (MS of light asphalt concrete that fabricated using expanded clay and had varied mix properties with Fuzzy Logic (FL were researched. With this aim, asphalt concrete samples that added expanded clay aggregate (EC in accordance with gradation determined in Highway Technical Specification, had different percentage of bitumen (POB (4.5%, 5%, 5.5%, 6%, 6.5%, 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.5% and unit weight (UW (1,75–1,87 (gr/cm3 were prepared and determined Marshall stabilities with Marshall test

  16. Predicting shape and stability of air-water interface on superhydrophobic surfaces comprised of pores with arbitrary shapes and depths

    Science.gov (United States)

    Emami, B.; Tafreshi, H. Vahedi; Gad-el-Hak, M.; Tepper, G. C.

    2012-01-01

    An integro-differential equation for the three dimensional shape of air-water interface on superhydrophobic surfaces comprised of pores with arbitrary shapes and depths is developed and used to predict the static critical pressure under which such surfaces depart from the non-wetting state. Our equation balances the capillary forces with the pressure of the air entrapped in the pores and that of the water over the interface. Stability of shallow and deep circular, elliptical, and polygonal pores is compared with one another and a general conclusion is drawn for designing pore shapes for superhydrophobic surfaces with maximum stability.

  17. Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity

    DEFF Research Database (Denmark)

    Rasmussen, Michael; Fenoy, Emilio; Harndahl, Mikkel

    2016-01-01

    of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding...... is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan....

  18. Dynamic data-driven prediction of instability in a swirl-stabilized combustor

    Directory of Open Access Journals (Sweden)

    Soumalya Sarkar

    2016-12-01

    Full Text Available Combustion instability poses a negative impact on the performance and structural durability of both land-based and aircraft gas turbine engines, and early detection of combustion instabilities is of paramount importance not only for performance monitoring and fault diagnosis, but also for initiating efficient decision and control of such engines. Combustion instability is, in general, characterized by self-sustained growth of large-amplitude pressure tones that are caused by a positive feedback arising from complex coupling of localized hydrodynamic perturbations, heat energy release, and acoustics of the combustor. This paper proposes a fast dynamic data-driven method for detecting early onsets of thermo-acoustic instabilities, where the underlying algorithms are built upon the concepts of symbolic time series analysis (STSA via generalization of D-Markov machine construction. The proposed method captures the spatiotemporal co-dependence among time series from heterogeneous sensors (e.g. pressure and chemiluminescence to generate an information-theoretic precursor, which is uniformly applicable across multiple operating regimes of the combustion process. The proposed method is experimentally validated on the time-series data, generated from a laboratory-scale swirl-stabilized combustor, while inducing thermo-acoustic instabilities for various protocols (e.g. increasing Reynolds number (Re at a constant fuel flow rate and reducing equivalence ratio at a constant air flow rate at varying air-fuel premixing levels. The underlying algorithms are developed based on D-Markov entropy rates, and the resulting instability precursor measure is rigorously compared with the state-of-the-art techniques in terms of its performance of instability prediction, computational complexity, and robustness to sensor noise.

  19. Predicting neuroendocrine tumor (carcinoid) neoplasia using gene expression profiling and supervised machine learning.

    Science.gov (United States)

    Drozdov, Ignat; Kidd, Mark; Nadler, Boaz; Camp, Robert L; Mane, Shrikant M; Hauso, Oyvind; Gustafsson, Bjorn I; Modlin, Irvin M

    2009-04-15

    A more accurate taxonomy of small intestinal (SI) neuroendocrine tumors (NETs) is necessary to accurately predict tumor behavior and prognosis and to define therapeutic strategy. In this study, the authors identified a panel of such markers that have been implicated in tumorigenicity, metastasis, and hormone production and hypothesized that transcript levels of the genes melanoma antigen family D2 (MAGE-D2), metastasis-associated 1 (MTA1), nucleosome assembly protein 1-like (NAP1L1), Ki-67 (a marker of proliferation), survivin, frizzled homolog 7 (FZD7), the Kiss1 metastasis suppressor (Kiss1), neuropilin 2 (NRP2), and chromogranin A (CgA) could be used to define primary SI NETs and to predict the development of metastases. Seventy-three clinically and World Health Organization pathologically classified NET samples (primary tumor, n = 44 samples; liver metastases, n = 29 samples) and 30 normal human enterochromaffin (EC) cell preparations were analyzed using real-time polymerase chain reaction. Transcript levels were normalized to 3 NET housekeeping genes (asparagine-linked glycosylation 9 or ALG9, transcription factor CP2 or TFCP2, and zinc finger protein 410 or ZNF410) using geNorm analysis. A predictive gene-based model was constructed using supervised learning algorithms from the transcript expression levels. Primary SI NETs could be differentiated from normal human EC cell preparations with 100% specificity and 92% sensitivity. Well differentiated NETs (WDNETs), well differentiated neuroendocrine carcinomas, and poorly differentiated NETs (PDNETs) were classified with a specificity of 78%, 78%, and 71%, respectively; whereas poorly differentiated neuroendocrine carcinomas were misclassified as either WDNETs or PDNETs. Metastases were predicted in all cases with 100% sensitivity and specificity. The current results indicated that gene expression profiling and supervised machine learning can be used to classify SI NET subtypes and accurately predict metastasis

  20. Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

    Science.gov (United States)

    Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

    2017-11-27

    Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly-targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely-measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely-applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen

  1. Using state diagrams for predicting colloidal stability of whey protein beverages.

    Science.gov (United States)

    Wagoner, Ty B; Ward, Loren; Foegeding, E Allen

    2015-05-06

    A method for evaluating aspects of colloidal stability of whey protein beverages after thermal treatment was established. Three state diagrams for beverages (pH 3-7) were developed representing protein solubility, turbidity, and macroscopic state after two ultrahigh-temperature (UHT) treatments. Key transitions of stability in the state diagrams were explored using electrophoresis and chromatography to determine aggregation propensities of β-lactoglobulin, α-lactalbumin, bovine serum albumin, and glycomacropeptide. The state diagrams present an overlapping view of high colloidal stability at pH 3 accompanied by high solubility of individual whey proteins. At pH 5, beverages were characterized by poor solubility, high turbidity, and aggregation/gelation of whey proteins with the exception of glycomacropeptide. Stability increased at pH 6, due to increased solubility of α-lactalbumin. The results indicate that combinations of state diagrams can be used to identify key regions of stability for whey protein containing beverages.

  2. Cg/Stability Map for the Reference H Cycle 3 Supersonic Transport Concept Along the High Speed Research Baseline Mission Profile

    Science.gov (United States)

    Giesy, Daniel P.; Christhilf, David M.

    1999-01-01

    A comparison is made between the results of trimming a High Speed Civil Transport (HSCT) concept along a reference mission profile using two trim modes. One mode uses the stabilator. The other mode uses fore and aft placement of the center of gravity. A comparison is make of the throttle settings (cruise segments) or the total acceleration (ascent and descent segments) and of the drag coefficient. The comparative stability of trimming using the two modes is also assessed by comparing the stability margins and the placement of the lateral and longitudinal eigenvalues.

  3. Prediction of euphotic depths and diffuse attenuation coefficients from absorption profiles: a model based on comparisons between vertical profiles of spectral absorption, spectral irradiance, and P

    Science.gov (United States)

    Zaneveld, J. Ronald V.; Pegau, Scott; Barnard, Andrew H.; Mueller, James L.; Maske, Helmut; Valdez, Eduardo; Lara-Lara, Ruben; Alvarez-Borrego, Saul

    1997-02-01

    A model is presented which predicts the diffuse attenuation coefficient of downwelling irradiance as a function of depth and the depth of the euphotic zone as based on the one percent level of photosynthetically active radiation from vertical profiles of spectral absorption and attenuation. The model is tested using data obtained in the Gulf of California. The modeled diffuse attenuation coefficients and PAR levels ar shown to have average errors of less than five percent when compared to the measured values.

  4. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2007-01-01

    the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance...... of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles. RESULTS: The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation...... by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic...

  5. Benchmarking and qualification of the NUFREQ-NPW code for best-estimate prediction of multichannel core stability margins

    Energy Technology Data Exchange (ETDEWEB)

    Taleyarkhan, R.; McFarlane, A.F.; Lahey, R.T. Jr.; Podowski, M.Z.

    1988-01-01

    The work described in this paper focuses on the development, verification, and benchmarking of the NUFREQ-NPW code at Westinghouse for best-estimate prediction of multichannel core stability margins in US boiling water reactors (BWRs). The NUFREQ-NPW code can allow for generalized three-dimensional core analyses of BWRs. The code was modified at Westinghouse to allow for a mixed-fuel-type multichannel core-wide stability analysis. One of the key distinguishing features of NUFREQ-NPW over other stability codes is that the analytical model allows for the system pressure perturbation as an external forcing function. This enables direct comparisons against pressure perturbation test data, instead of inferring equivalent information via curve fitting of other transfer functions. The results of comparisons with experimental data using the Westinghouse methodology, which is based on the NUFREQ-NPW code, demonstrate the best-estimate predictive capability for BWR core stability margins. The methodology is thus suitable for design and licensing applications.

  6. Theoretical prediction of familial amyotrophic lateral sclerosis missense mutation effects on Cu/Zn superoxide dismutase structural stability

    Energy Technology Data Exchange (ETDEWEB)

    Potier, M.; Tu, Y. [Universite de Montreal, Quebec (Canada)

    1994-09-01

    Cu/Zn superoxide dismutase (SOD) deficiency is associated with the progressive paralytic disorder familial amyotrophic lateral sclerosis (FALS). Fifteen missense mutations in the SOD gene were identified in several patients. These mutations may prevent correct promoter folding or hamper homodimer formation necessary for SOD activity. To understand the effect of the missense mutations on SOD structure and function, we used a theoretical analysis of structural effects based on two predictive methods using the modeled tertiary structure of human SOD. The first method uses the TORSO program which optimizes amino acid side-chains repacking in both wild-type and mutant SODs and calculates protein internal packing energy. The second method uses a hydrophobicity scale of the amino acid residues and considers both solvent accessibility and hydrophobic nature of residue substitutions to compute a stabilization energy change ({delta}E). These predictive methods have been tested in 187 single and multiple missense mutants of 8 proteins (T4 lysozyme, human carbonic anhydrase II, chymotrypsin inhibitor 2, f1 gene V protein, barnase, {lambda}-repressor, chicken and human lysozymes) with experimentally determined thermostability. The overall prediction accuracy with these proteins was 88%. Analysis of FALS missense mutations {delta}E predicts that 14 of 15 mutations destabilize the SOD structure. The other missense mutation is located at the homodimer interface and may hinder dimer formation. This approach is applicable to any protein with known tertiary structure to predict missense mutation effects on protein stability.

  7. Predictability and stability of refraction with increasing optical zone diameter in hyperopic LASIK

    Directory of Open Access Journals (Sweden)

    Mostafa A El-Helw

    2010-05-01

    Full Text Available Mostafa A El-Helw, Ahmed M EmarahCairo University, Cairo, EgyptObjective: We undertook a prospective nonrandomized study to assess refractive outcome and patient satisfaction with hyperopic laser in situ keratomileusis (LASIK using variable optical zone diameters in correction of hyperopia of more than 4.00 diopters.Methods: Fourteen adults (comprising 28 hyperopic eyes underwent hyperopic LASIK correction for hyperopia of more than 4.00 diopters. The sample was divided into two groups. Group 1 included the right eyes of the 14 patients who underwent hyperopic LASIK using a 6.5 mm optical zone diameter. Group 2 comprised the left eyes of the same patients with the only difference being that the optical zone diameter was 6.0 mm.Results: The mean age of the patients was 36.42 ± 5.10 years. Group 1 eyes had a median (range preoperative uncorrected visual acuity (UCVA of 0.79 (0.52 and best-corrected visual acuity (BCVA of 0.15 (0.08. Group 2 had a median preoperative UCVA of 0.79 (0.60 and BCVA of 0.15 (0.08. The median postoperative UCVA in Group 1 was 0.17 (0.21 and BCVA was 0.15 (0.13. In Group 2, the median postoperative UCVA was 0.30 (0.32 and BCVA was 0.15 (0.26. Group 1 had a median preoperative refraction of +5.37 (1.75 diopters and the median postoperative refraction at one week was −0.23 (1.25 diopters, at three months was +0.75 (0.75 diopters, and at six months was +0.75 (1.00 diopters. Group 2 had a median preoperative refraction of +5.00 (1.75 diopters, and the median postoperative refraction at one week was +0.13 (1.5 diopters, at three months was +1.00 (0.75 diopters and at six months +1.25 (1.25 diopters. The difference was statistically significant between groups 1 and 2. The difference within each group was also significant. Group 1 eyes were stabilizing after the three-month period in contrast with Group 2 in which the refractive changes continued throughout the follow-up period.Conclusion: Larger optical zone diameter in

  8. Longitudinal Stability of Social Competence Indicators in a Portuguese Sample: Q-Sort Profiles of Social Competence, Measures of Social Engagement, and Peer Sociometric Acceptance

    Science.gov (United States)

    Santos, António J.; Vaughn, Brian E.; Peceguina, Inês; Daniel, João R.

    2014-01-01

    This study examines the temporal stability (over 3 years) of individual differences in 3 domains relevant to preschool children's social competence: social engagement/motivation, profiles of behavior and personality attributes characteristic of socially competent young children, and peer acceptance. Each domain was measured with multiple…

  9. Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration

    Directory of Open Access Journals (Sweden)

    Thongchart Kerdphol

    2017-05-01

    Full Text Available Renewable energy sources (RESs, such as wind and solar generations, equip inverters to connect to the microgrids. These inverters do not have any rotating mass, thus lowering the overall system inertia. This low system inertia issue could affect the microgrid stability and resiliency in the situation of uncertainties. Today’s microgrids will become unstable if the capacity of RESs become larger and larger, leading to the weakening of microgrid stability and resilience. This paper addresses a new concept of a microgrid control incorporating a virtual inertia system based on the model predictive control (MPC to emulate virtual inertia into the microgrid control loop, thus stabilizing microgrid frequency during high penetration of RESs. The additional controller of virtual inertia is applied to the microgrid, employing MPC with virtual inertia response. System modeling and simulations are carried out using MATLAB/Simulink® software. The simulation results confirm the superior robustness and frequency stabilization effect of the proposed MPC-based virtual inertia control in comparison to the fuzzy logic system and conventional virtual inertia control in a system with high integration of RESs. The proposed MPC-based virtual inertia control is able to improve the robustness and frequency stabilization of the microgrid effectively.

  10. Ideal MHD Stability Prediction and Required Power for EAST Advanced Scenario

    Science.gov (United States)

    Chen, Junjie; Li, Guoqiang; Qian, Jinping; Liu, Zixi

    2012-11-01

    The Experimental Advanced Superconducting Tokamak (EAST) is the first fully superconducting tokamak with a D-shaped cross-sectional plasma presently in operation. The ideal magnetohydrodynamic (MHD) stability and required power for the EAST advanced tokamak (AT) scenario with negative central shear and double transport barrier (DTB) are investigated. With the equilibrium code TOQ and stability code GATO, the ideal MHD stability is analyzed. It is shown that a moderate ratio of edge transport barriers' (ETB) height to internal transport barriers' (ITBs) height is beneficial to ideal MHD stability. The normalized beta βN limit is about 2.20 (without wall) and 3.70 (with ideal wall). With the scaling law of energy confinement time, the required heating power for EAST AT scenario is calculated. The total heating power Pt increases as the toroidal magnetic field BT or the normalized beta βN is increased.

  11. NETMHCSTAB - predicting stability of peptide-MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery

    DEFF Research Database (Denmark)

    Jørgensen, Kasper W.; Rasmussen, Michael; Buus, Søren

    2013-01-01

    Major histocompatibility complex class I (MHC-I) molecules play an essential role in the cellular immune response, presenting peptides to cytotoxic T lymphocytes (CTLs) allowing the immune system to scrutinize ongoing intracellular production of proteins. In the early 1990s, immunogenicity...... and stability of the peptide-MHC-I (pMHC-I) complex were shown to be correlated. At that time, measuring stability was cumbersome and time consuming and only small data sets were analysed. Here, we investigate this fairly unexplored area on a large scale compared with earlier studies. A recent small-scale study...... demonstrated that pMHC-I complex stability was a better correlate of CTL immunogenicity than peptide-MHC-I affinity. We here extended this study and analysed a total of 5509 distinct peptide stability measurements covering 10 different HLA class I molecules. Artificial neural networks were used to construct...

  12. Profile changes and stability following distraction osteogenesis with rigid external distraction in adult cleft lip and palate deformities

    Directory of Open Access Journals (Sweden)

    Jaeson M Painatt

    2017-01-01

    Full Text Available Objectives: The objective of this study is to analyze the hard and soft-tissue profile changes as well as the upper airway changes after distraction osteogenesis (DO using rigid external distraction device in adult cleft lip and palate (CLP patients. The study also evaluates the stability of the surgical result. Materials and Methods: Three lateral cephalometric radiographs were taken: Predistraction (T1, postdistraction (T2, and 1 year after distractor removal (T3. The treatment changes (T1 vs. T2 and the stability (T2 vs. T3 were analyzed. The overall treatment changes after 1 year were also evaluated (T1 vs. T3. The lateral cephalograms were digitally analyzed with the help of software named Dolphin. Statistical Analysis Used: Wilcoxon Signed-Ranks test was used, and the probability value (P value of 0.05 was considered as statistically significant level. Results: Eleven adult patients with CLP were retrospectively analyzed. After distraction, there was a significant mean maxillary advancement of 14 mm (P < 0.01 from a T1 value of 73.54 ± 10.38 to a T2 value of 88.2 ± 10.49. The lower facial height and the incisor exposure were significantly increased. The nasolabial angle had a significant improvement of 24.5° (P < 0.01 from a T1 value of 56.6 ± 21.03 to a T2 value of 81.18 ± 14.4.The upper airway was significantly improved by 3.7 mm (P < 0.01 with a T1 value of 13.5 ± 3.8 to a T2 value of 17.2 ± 3.66. After 1-year follow-up, there was a significant maxillary relapse of 3.20 mm (P < 0.05 from a T2 value of 8.29 ± 6.84 to a T3 value of 5.09 ± 5.59. However, the soft-tissue profile and upper airway remained stable. Conclusion: The clinician should have an understanding of the related hard and soft tissues as well as airway changes which may assist him when planning for maxillary advancement for CLP patients with DO. There were significant improvements immediately after distraction, but during the 1-year follow-up, some relapse was

  13. Integrated community profiling indicates long-term temporal stability of the predominant faecal microbiota in captive cheetahs.

    Directory of Open Access Journals (Sweden)

    Anne A M J Becker

    Full Text Available Understanding the symbiotic relationship between gut microbes and their animal host requires characterization of the core microbiota across populations and in time. Especially in captive populations of endangered wildlife species such as the cheetah (Acinonyx jubatus, this knowledge is a key element to enhance feeding strategies and reduce gastrointestinal disorders. In order to investigate the temporal stability of the intestinal microbiota in cheetahs under human care, we conducted a longitudinal study over a 3-year period with bimonthly faecal sampling of 5 cheetahs housed in two European zoos. For this purpose, an integrated 16S rRNA DGGE-clone library approach was used in combination with a series of real-time PCR assays. Our findings disclosed a stable faecal microbiota, beyond intestinal community variations that were detected between zoo sample sets or between animals. The core of this microbiota was dominated by members of Clostridium clusters I, XI and XIVa, with mean concentrations ranging from 7.5-9.2 log10 CFU/g faeces and with significant positive correlations between these clusters (P<0.05, and by Lactobacillaceae. Moving window analysis of DGGE profiles revealed 23.3-25.6% change between consecutive samples for four of the cheetahs. The fifth animal in the study suffered from intermediate episodes of vomiting and diarrhea during the monitoring period and exhibited remarkably more change (39.4%. This observation may reflect the temporary impact of perturbations such as the animal's compromised health, antibiotic administration or a combination thereof, which temporarily altered the relative proportions of Clostridium clusters I and XIVa. In conclusion, this first long-term monitoring study of the faecal microbiota in feline strict carnivores not only reveals a remarkable compositional stability of this ecosystem, but also shows a qualitative and quantitative similarity in a defined set of faecal bacterial lineages across the five

  14. Predicting miRNA Targets by Integrating Gene Regulatory Knowledge with Expression Profiles.

    Directory of Open Access Journals (Sweden)

    Weijia Zhang

    Full Text Available microRNAs (miRNAs play crucial roles in post-transcriptional gene regulation of both plants and mammals, and dysfunctions of miRNAs are often associated with tumorigenesis and development through the effects on their target messenger RNAs (mRNAs. Identifying miRNA functions is critical for understanding cancer mechanisms and determining the efficacy of drugs. Computational methods analyzing high-throughput data offer great assistance in understanding the diverse and complex relationships between miRNAs and mRNAs. However, most of the existing methods do not fully utilise the available knowledge in biology to reduce the uncertainty in the modeling process. Therefore it is desirable to develop a method that can seamlessly integrate existing biological knowledge and high-throughput data into the process of discovering miRNA regulation mechanisms.In this article we present an integrative framework, CIDER (Causal miRNA target Discovery with Expression profile and Regulatory knowledge, to predict miRNA targets. CIDER is able to utilise a variety of gene regulation knowledge, including transcriptional and post-transcriptional knowledge, and to exploit gene expression data for the discovery of miRNA-mRNA regulatory relationships. The benefits of our framework is demonstrated by both simulation study and the analysis of the epithelial-to-mesenchymal transition (EMT and the breast cancer (BRCA datasets. Our results reveal that even a limited amount of either Transcription Factor (TF-miRNA or miRNA-mRNA regulatory knowledge improves the performance of miRNA target prediction, and the combination of the two types of knowledge enhances the improvement further. Another useful property of the framework is that its performance increases monotonically with the increase of regulatory knowledge.

  15. Solid Waste Biodegradation Enhancements and the Evaluation of Analytical Methods Used to Predict Waste Stability

    OpenAIRE

    Kelly, Ryan J.

    2002-01-01

    Conventional landfills are built to dispose of the increasing amount of municipal solid waste (MSW) generated each year. A relatively new type of landfill, called a bioreactor landfill, is designed to optimize the biodegradation of the contained waste to stabilized products. Landfills with stabilized waste pose little threat to the environment from ozone depleting gases and groundwater contamination. Limited research has been done to determine the importance of biodegradation enhancement tech...

  16. Effect of family structure and TPH2 G-703T on the stability of dysregulation profile throughout adolescence.

    Science.gov (United States)

    Nobile, Maria; Bianchi, Valentina; Monzani, Dario; Beri, Silvana; Bellina, Monica; Greco, Andrea; Colombo, Paola; Tesei, Alessandra; Caldirola, Daniela; Giorda, Roberto; Perna, Giampaolo; Molteni, Massimo

    2016-01-15

    Two different polymorphisms (TPH2 G-703T and 5-HTTLPR) involved in the serotonergic pathway have been reported to play a role, both alone and in interaction with the environment, in early and adult emotion regulation. As most of these studies are cross-sectional, we know little about the impact of these polymorphisms over time, particularly during adolescence. Because we were interested in the effects of these polymorphisms and environment (i.e., family structure) at different time-points on the emotional dysregulation profile, we performed a path analysis model in a general adolescent population sample of a five-year follow-up study. We found a high stability of Dysregulation Profile problems independently from the examined allelic variants. We also found that early family structure directly influences the levels of dysregulation problems in early adolescence, both alone and in interaction with TPH2, suggesting the presence of a gene-environment interaction effect. Furthermore, we found that in adolescents homozygous for the TPH2 G allele, the effect of the early family structure remains active during late adolescence, albeit mediated by earlier emotional problems. The high attrition rate, the use of only one source on behavioral problems of adolescents, and the focus on a single polymorphism in the investigated genes could limit the generalizability of the present results. These results suggest that early family structure could play a significant role in the development and maintenance of emotional and behavioral problems not only in early adolescence but also in late-adolescence, although this effect was mediated and moderated by behavioral and genetic variables. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database

    DEFF Research Database (Denmark)

    Deng, Fan; Knadel, Maria; Peng, Yi

    This study focuses on the application of the Danish national soil Visible Near Infrared Re-flectance spectroscopy (NIRs) database for predicting SOC in a field. The Conditioned Latin hypercube sam-pling (cLHS) method was used for the selection of 120 soil profiles based on DualEM21s and DEM data...

  18. DIGEP-Pred: web service for in silico prediction of drug-induced gene expression profiles based on structural formula.

    Science.gov (United States)

    Lagunin, Alexey; Ivanov, Sergey; Rudik, Anastasia; Filimonov, Dmitry; Poroikov, Vladimir

    2013-08-15

    Experimentally found gene expression profiles are used to solve different problems in pharmaceutical studies, such as drug repositioning, resistance, toxicity and drug-drug interactions. A special web service, DIGEP-Pred, for prediction of drug-induced changes of gene expression profiles based on structural formulae of chemicals has been developed. Structure-activity relationships for prediction of drug-induced gene expression profiles were determined by Prediction of Activity Spectra for Substances (PASS) software. Comparative Toxicogenomics Database with data on the known drug-induced gene expression profiles of chemicals was used to create mRNA- and protein-based training sets. An average prediction accuracy for the training sets (ROC AUC) calculated by leave-one-out cross-validation on the basis of mRNA data (1385 compounds, 952 genes, 500 up- and 475 down-regulations) and protein data (1451 compounds, 139 genes, 93 up- and 55 down-regulations) exceeded 0.85. Freely available on the web at http://www.way2drug.com/GE.

  19. The Impact of Mission Profile Models on the Predicted Lifetime of IGBT Modules in the Modular Multilevel Converter

    DEFF Research Database (Denmark)

    Zhang, Yi; Wang, Huai; Wang, Zhongxu

    2017-01-01

    The reliability aspect study of Modular Multilevel Converter (MMC) is of great interest in industry applications, such as offshore wind. Lifetime prediction of key components is an important tool to design MMC with fulfilled reliability specifications. While many efforts have been made...... and electrical power modeling methods on the estimated lifetime of IGBT modules in an MMC for offshore wind power application. In a 30 MW MMC case study, an annual wind speed profile with a resolution of 1 s/data, 10 minute/data, and 1 hour/data are considered, respectively. A method to re-generate higher...... used in the MMC, resulting in significant differences. The study serves as a first step to quantify the impact of mission profile modeling on lifetime prediction, and to provide a guideline on mission profile collection for the presented application....

  20. Metabolite Profile of Cervicovaginal Fluids from Early Pregnancy Is Not Predictive of Spontaneous Preterm Birth

    Directory of Open Access Journals (Sweden)

    Melinda M. Thomas

    2015-11-01

    Full Text Available In our study, we used a mass spectrometry-based metabolomic approach to search for biomarkers that may act as early indicators of spontaneous preterm birth (sPTB. Samples were selected as a nested case-control study from the Screening for Pregnancy Endpoints (SCOPE biobank in Auckland, New Zealand. Cervicovaginal swabs were collected at 20 weeks from women who were originally assessed as being at low risk of sPTB. Samples were analysed using gas chromatography-mass spectrometry (GC-MS. Despite the low amount of biomass (16–23 mg, 112 compounds were detected. Statistical analysis showed no significant correlations with sPTB. Comparison of reported infection and plasma inflammatory markers from early pregnancy showed two inflammatory markers were correlated with reported infection, but no correlation with any compounds in the metabolite profile was observed. We hypothesise that the lack of biomarkers of sPTB in the cervicovaginal fluid metabolome is simply because it lacks such markers in early pregnancy. We propose alternative biofluids be investigated for markers of sPTB. Our results lead us to call for greater scrutiny of previously published metabolomic data relating to biomarkers of sPTB in cervicovaginal fluids, as the use of small, high risk, or late pregnancy cohorts may identify metabolite biomarkers that are irrelevant for predicting risk in normal populations.

  1. Metataxonomic profiling and prediction of functional behaviour of wheat straw degrading microbial consortia.

    Science.gov (United States)

    Jiménez, Diego Javier; Dini-Andreote, Francisco; van Elsas, Jan Dirk

    2014-01-01

    Mixed microbial cultures, in which bacteria and fungi interact, have been proposed as an efficient way to deconstruct plant waste. The characterization of specific microbial consortia could be the starting point for novel biotechnological applications related to the efficient conversion of lignocellulose to cello-oligosaccharides, plastics and/or biofuels. Here, the diversity, composition and predicted functional profiles of novel bacterial-fungal consortia are reported, on the basis of replicated aerobic wheat straw enrichment cultures. In order to set up biodegradative microcosms, microbial communities were retrieved from a forest soil and introduced into a mineral salt medium containing 1% of (un)treated wheat straw. Following each incubation step, sequential transfers were carried out using 1 to 1,000 dilutions. The microbial source next to three sequential batch cultures (transfers 1, 3 and 10) were analyzed by bacterial 16S rRNA gene and fungal ITS1 pyrosequencing. Faith's phylogenetic diversity values became progressively smaller from the inoculum to the sequential batch cultures. Moreover, increases in the relative abundances of Enterobacteriales, Pseudomonadales, Flavobacteriales and Sphingobacteriales were noted along the enrichment process. Operational taxonomic units affiliated with Acinetobacter johnsonii, Pseudomonas putida and Sphingobacterium faecium were abundant and the underlying strains were successfully isolated. Interestingly, Klebsiella variicola (OTU1062) was found to dominate in both consortia, whereas K. variicola-affiliated strains retrieved from untreated wheat straw consortia showed endoglucanase/xylanase activities. Among the fungal players with high biotechnological relevance, we recovered members of the genera Penicillium, Acremonium, Coniochaeta and Trichosporon. Remarkably, the presence of peroxidases, alpha-L-fucosidases, beta-xylosidases, beta-mannases and beta-glucosidases, involved in lignocellulose degradation, was indicated

  2. Term-tissue specific models for prediction of gene ontology biological processes using transcriptional profiles of aging in drosophila melanogaster

    Directory of Open Access Journals (Sweden)

    Zou Sige

    2008-02-01

    Full Text Available Abstract Background Predictive classification on the base of gene expression profiles appeared recently as an attractive strategy for identifying the biological functions of genes. Gene Ontology (GO provides a valuable source of knowledge for model training and validation. The increasing collection of microarray data represents a valuable source for generating functional hypotheses of uncharacterized genes. Results This study focused on using support vector machines (SVM to predict GO biological processes from individual or multiple-tissue transcriptional profiles of aging in Drosophila melanogaster. Ten-fold cross validation was implemented to evaluate the prediction. One-tail Fisher's exact test was conducted on each cross validation and multiple testing was addressed using BH FDR procedure. The results showed that, of the 148 pursued GO biological processes, fifteen terms each had at least one model with FDR-adjusted p-value (Adj.p Conclusion We proposed the concept of term-tissue specific models indicating the fact that the major part of the optimized prediction models was trained from individual tissue data. Furthermore, we observed that the memberships of the genes involved in all the three pursued children biological processes on mitochondrial electron transport could be predicted from the transcriptional profiles of aging (Adj.p

  3. Stability in vitiligo: Is there a perfect way to predict it?

    Directory of Open Access Journals (Sweden)

    Kanika Sahni

    2013-01-01

    Full Text Available Stability is a hard-to-define concept in the setting of vitiligo, but is nonetheless extremely crucial to the planning of treatment regimens and also in prognosticating for the patient. There are several ways to judge stability in vitiligo, which include clinical features and, recently, many biochemical, cytological and ultrastructural correlates of the same. These recent advances help in not only in prognosticating individual patients but also in elucidating some of the mechanisms for the pathogenesis of vitiligo, including melanocytorrhagy and oxidative damage to melanocytes.

  4. Prediction of glycated hemoglobin levels at 3 months after metabolic surgery based on the 7-day plasma metabolic profile.

    Directory of Open Access Journals (Sweden)

    Hyuk Nam Kwon

    Full Text Available Metabolic surgery has been shown to provide better glycemic control for type 2 diabetes than conventional therapies. Still, the outcomes of the surgery are variable, and prognostic markers reflecting the metabolic changes by the surgery are yet to be established. NMR-based plasma metabolomics followed by multivariate regression was used to test the correlation between the metabolomic profile at 7-days after surgery and glycated hemoglobin (HbA1c levels at 3-months (and up to 12 months with less patients, and to identify the relevant markers. Metabolomic profiles at 7-days could differentiate the patients according to the HbA1c improvement status at 3-months. The HbA1c values were predicted based on the metabolomics profile with partial least square regression, and found to be correlated with the observed values. Metabolite analysis suggested that 3-Hydroxybutyrate (3-HB and glucose contributes to this prediction, and the [3-HB]/[glucose] exhibited a modest to good correlation with the HbA1c level at 3-months. The prediction of 3-month HbA1c using 7-day metabolomic profile and the suggested new criterion [3-HB]/[glucose] could augment current prognostic modalities and help clinicians decide if drug therapy is necessary.

  5. Reading Others’ Emotions: The Role of Intuitive Judgments in Predicting Marital Satisfaction, Quality, and Stability

    OpenAIRE

    Waldinger, Robert J.; Hauser, Stuart T.; Schulz, Marc S.; Allen, Joseph P.; Crowell, Judith A.

    2004-01-01

    This study examined links between emotion expression in couple interactions and marital quality and stability. Core aspects of emotion expression in marital interactions were identified with the use of naïve observational coding by multiple raters. Judges rated 47 marital discussions with 15 emotion descriptors. Coders’ pooled ratings yielded good reliability on 4 types of emotio...

  6. A multidimensional stability model for predicting shallow landslide size and shape across landscapes

    Science.gov (United States)

    David G. Milledge; Dino Bellugi; Jim A. McKean; Alexander L. Densmore; William E. Dietrich

    2014-01-01

    The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but...

  7. Predicting nicotine dependence profiles among adolescent smokers: the roles of personal and social-environmental factors in a longitudinal framework

    Directory of Open Access Journals (Sweden)

    Kleinjan Marloes

    2012-03-01

    Full Text Available Abstract Background Although several studies have reported that symptoms of nicotine dependence can occur after limited exposure to smoking, the majority of research on nicotine dependence has focused on adult smokers. Insufficient knowledge exists regarding the epidemiology and aetiology of nicotine dependence among adolescent smokers. The objective of the present study is to identify the effects of theoretically driven social and individual predictors of nicotine dependence symptom profiles in a population-based sample of adolescent smokers. Method A longitudinal study among 6,783 adolescents (12 to 14 years old at baseline was conducted. In the first and second year of secondary education, personality traits and exposure to smoking in the social environment were assessed. Two and a half years later, adolescents' smoking status and nicotine dependence symptom profiles were assessed. A total of 796 adolescents were identified as smokers and included in the analyses. Results At follow-up, four distinct dependence symptom profiles were identified: low cravings only, high cravings and withdrawal, high cravings and behavioural dependence, and overall highly dependent. Personality traits of neuroticism and extraversion did not independently predict nicotine dependence profiles, whereas exposure to smoking in the social environment posed a risk for the initial development of nicotine dependence symptoms. However, in combination with environmental exposure to smoking, extraversion and neuroticism increased the risk of developing more severe dependence symptom profiles. Conclusions Nicotine dependence profiles are predicted by interactions between personal and environmental factors. These insights offer important directions for tailoring interventions to prevent the onset and escalation of nicotine dependence. Opportunities for intervention programs that target individuals with a high risk of developing more severe dependence symptom profiles are

  8. A circulating TH2 cytokines profile predicts survival in patients with resectable pancreatic adenocarcinoma

    Science.gov (United States)

    Piro, Geny; Carbone, Carmine; Frizziero, Melissa; Malleo, Giuseppe; Zanini, Silvia; Casolino, Raffaella; Santoro, Raffaela; Mina, Maria Mihaela; Zecchetto, Camilla; Merz, Valeria; Scarpa, Aldo; Bassi, Claudio; Tortora, Giampaolo

    2017-01-01

    ABSTRACT Surgery is the only potentially curative option for patients with pancreatic ductal adenocarcinoma (PDAC), but metastatic relapse remains common. We hypothesized that the expression levels of inflammatory cytokines could predict recurrence of PDAC, thus allowing to select patients who most likely could benefit from surgical resection. We prospectively collected plasma at diagnosis from 287 patients with pancreatic resectable neoplasms. The expression levels of 23 cytokines were measured in 90 patients with PDAC by using a multiplex analyte profiling assay. Levels higher than cutoff identified of the TH2 cytokines interleukin (IL)4, IL5, IL6 of macrophage inflammatory protein (MIP)1α, granulocyte-macrophage colony-stimulating factor (GM-CSF), and monocyte chemoattractant protein (MCP)1, and of IL17α, IFNγ-induced protein (IP)10, and IL1b were significantly associated with a shorter median OS. In particular, levels of IL4 and IP10 higher than cutoff identified, and level of TH1 cytokines TNFα and INFγ, and of IL9 and IL1Rα lower than cutoff identified were significantly associated with a shorter DFS. In the multivariate analysis, high IP10 was confirmed as negatively associated with OS (HR = 3.097, p = 0.014) and IL4 and TNFα remain negatively (HR = 2.75, p = 0.002) and positively (HR = 0.224, p = 0.049) associated with DFS, respectively. Simultaneous expression of low IL4 and high TNFα identified patients with best prognosis (HR = 0.313, p < 0.0001). In conclusion, we demonstrated that, among a series of cytokines, IL4 is the most significant independent prognostic factor for DFS in resectable PDAC patients, and it could be useful to select patients with high risk of early recurrence who may avoid an unnecessary resection. PMID:28932629

  9. Inflammatory and metalloproteinases profiles predict three-month poor outcomes in ischemic stroke treated with thrombolysis.

    Science.gov (United States)

    Gori, Anna Maria; Giusti, Betti; Piccardi, Benedetta; Nencini, Patrizia; Palumbo, Vanessa; Nesi, Mascia; Nucera, Antonia; Pracucci, Giovanni; Tonelli, Paolina; Innocenti, Eleonora; Sereni, Alice; Sticchi, Elena; Toni, Danilo; Bovi, Paolo; Guidotti, Mario; Tola, Maria Rosaria; Consoli, Domenico; Micieli, Giuseppe; Tassi, Rossana; Orlandi, Giovanni; Sessa, Maria; Perini, Francesco; Delodovici, Maria Luisa; Zedde, Maria Luisa; Massaro, Francesca; Abbate, Rosanna; Inzitari, Domenico

    2017-09-01

    Inflammatory mediators and metalloproteinases are altered in acute ischemic stroke (AIS) and play a detrimental effect on clinical severity and hemorrhagic transformation of the ischemic brain lesion. Using data from the Italian multicenter observational MAGIC (MArker bioloGici nell'Ictus Cerebrale) Study, we evaluated the effect of inflammatory and metalloproteinases profiles on three-month functional outcome, hemorrhagic transformation and mortality in 327 patients with AIS treated with intravenous thrombolys in according to SITS-MOST (Safe Implementation of Thrombolysis in Stroke-MOnitoring STudy) criteria. Circulating biomarkers were assessed at baseline and 24 h after thrombolysis. Adjusting for age, sex, baseline glycemia and National Institute of Health Stroke Scale, history of atrial fibrillation or congestive heart failure, and of inflammatory diseases or infections, baseline alpha-2macroglobulin (A2M), baseline serum amyloid protein (SAP) and pre-post tissue-plasminogen activator (tPA) variations (Δ) of metalloproteinase 9, remained significantly and independently associated with three-month death [OR (95% CI):A2M:2.99 (1.19-7.53); SAP:5.46 (1.64-18.74); Δmetalloproteinase 9:1.60 (1.12-2.27)]. The addition of baseline A2M and Δmetalloproteinase 9 or baseline SAP and Δmetalloproteinase 9 (model-2 or model-3) to clinical variables (model-1) significantly improved the area under curve for prediction of death [model-2 with A2M: p = 0.0205; model-3 with SAP: p = 0.001]. In conclusion, among AIS patients treated with thrombolysis, circulating A2M, SAP and Δmetalloproteinase 9 are independent markers of poor outcome. These results may prompt controlled clinical research about agents antagonizing their effect.

  10. The clinical utility of lipid profile and positive troponin in predicting future cardiac events

    OpenAIRE

    Arun Kumar; Brijesh Sathian

    2012-01-01

    Objective: To study the usefulness of traditional lipid profile levels in screening subjects who had developed chest pain due to cardiac event as indicated by a positive troponin I (TnI) test. Methods: In this retrospective study data of the 740 patients presented to the emergency department with symptoms of cardiac ischemia that underwent both troponin and lipid profiles tests were compared with the lipid profiles of 411 normal healthy subjects (controls). The troponin was det...

  11. Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

    Directory of Open Access Journals (Sweden)

    Banjanovic-Mehmedovic Lejla

    2016-01-01

    Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

  12. Predicting DNA-binding amino acid residues from electrostatic stabilization upon mutation to Asp/Glu and evolutionary conservation.

    Science.gov (United States)

    Chen, Yao Chi; Wu, Chih Yuan; Lim, Carmay

    2007-05-15

    Binding of polyanionic DNA depends on the cluster of electropositive atoms in the binding site of a DNA-binding protein. Such a cluster of electropositive protein atoms would be electrostatically unfavorable without stabilizing interactions from the respective electronegative DNA atoms and would likely be evolutionary conserved due to its critical biological role. Consequently, our strategy for predicting DNA-binding residues is based on detecting a cluster of evolutionary conserved surface residues that are electrostatically stabilized upon mutation to negatively charged Asp/Glu residues. The method requires as input the protein structure and sufficient sequence homologs to define each residue's relative conservation, and it yields as output experimentally testable residues that are predicted to bind DNA. By incorporating characteristic DNA-binding site features (i.e., electrostatic strain and amino acid conservation), the new method yields a prediction accuracy of 83%, which is much higher than methods based on only electrostatic strain (57%) or conservation alone (50%). It is also less sensitive to protein conformational changes upon DNA binding than methods that mainly depend on the 3D protein structure. 2007 Wiley-Liss, Inc.

  13. Whole-brain grey matter density predicts balance stability irrespective of age and protects older adults from falling.

    Science.gov (United States)

    Boisgontier, Matthieu P; Cheval, Boris; van Ruitenbeek, Peter; Levin, Oron; Renaud, Olivier; Chanal, Julien; Swinnen, Stephan P

    2016-03-01

    Functional and structural imaging studies have demonstrated the involvement of the brain in balance control. Nevertheless, how decisive grey matter density and white matter microstructural organisation are in predicting balance stability, and especially when linked to the effects of ageing, remains unclear. Standing balance was tested on a platform moving at different frequencies and amplitudes in 30 young and 30 older adults, with eyes open and with eyes closed. Centre of pressure variance was used as an indicator of balance instability. The mean density of grey matter and mean white matter microstructural organisation were measured using voxel-based morphometry and diffusion tensor imaging, respectively. Mixed-effects models were built to analyse the extent to which age, grey matter density, and white matter microstructural organisation predicted balance instability. Results showed that both grey matter density and age independently predicted balance instability. These predictions were reinforced when the level of difficulty of the conditions increased. Furthermore, grey matter predicted balance instability beyond age and at least as consistently as age across conditions. In other words, for balance stability, the level of whole-brain grey matter density is at least as decisive as being young or old. Finally, brain grey matter appeared to be protective against falls in older adults as age increased the probability of losing balance in older adults with low, but not moderate or high grey matter density. No such results were observed for white matter microstructural organisation, thereby reinforcing the specificity of our grey matter findings. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Relative drifts and stability of satellite and ground-based stratospheric ozone profiles at NDACC lidar stations

    Directory of Open Access Journals (Sweden)

    P. J. Nair

    2012-06-01

    Full Text Available The long-term evolution of stratospheric ozone at different stations in the low and mid-latitudes is investigated. The analysis is performed by comparing the collocated profiles of ozone lidars, at the northern mid-latitudes (Meteorological Observatory Hohenpeißenberg, Haute-Provence Observatory, Tsukuba and Table Mountain Facility, tropics (Mauna Loa Observatory and southern mid-latitudes (Lauder, with ozonesondes and space-borne sensors (SBUV(/2, SAGE II, HALOE, UARS MLS and Aura MLS, extracted around the stations. Relative differences are calculated to find biases and temporal drifts in the measurements. All measurement techniques show their best agreement with respect to the lidar at 20–40 km, where the differences and drifts are generally within ±5% and ±0.5% yr−1, respectively, at most stations. In addition, the stability of the long-term ozone observations (lidar, SBUV(/2, SAGE II and HALOE is evaluated by the cross-comparison of each data set. In general, all lidars and SBUV(/2 exhibit near-zero drifts and the comparison between SAGE II and HALOE shows larger, but insignificant drifts. The RMS of the drifts of lidar and SBUV(/2 is 0.22 and 0.27% yr−1, respectively at 20–40 km. The average drifts of the long-term data sets, derived from various comparisons, are less than ±0.3% yr−1 in the 20–40 km altitude at all stations. A combined time series of the relative differences between SAGE II, HALOE and Aura MLS with respect to lidar data at six sites is constructed, to obtain long-term data sets lasting up to 27 years. The relative drifts derived from these combined data are very small, within ±0.2% yr−1.

  15. A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

    Science.gov (United States)

    2013-08-01

    will profile tumors for the 60 genes of the BRCAness profile using the NanoString nCounter Platform. The NanoString nCounter has several advantages...a linear dynamic range of over 500-fold. We have now completed the Nanostring nCounter experiments for these samples and we will proceed with the

  16. Reading others emotions: The role of intuitive judgments in predicting marital satisfaction, quality, and stability.

    Science.gov (United States)

    Waldinger, Robert J; Hauser, Stuart T; Schulz, Marc S; Allen, Joseph P; Crowell, Judith A

    2004-03-01

    This study examined links between emotion expression in couple interactions and marital quality and stability. Core aspects of emotion expression in marital interactions were identified with the use of naive observational coding by multiple raters. Judges rated 47 marital discussions with 15 emotion descriptors. Coders' pooled ratings yielded good reliability on 4 types of emotion expression: hostility, distress, empathy, and affection. These 4 types were linked with concurrent marital satisfaction and interviewer ratings of marital adjustment as well as with marital stability at a 5-year follow-up. The study also examined the extent to which naive judges' ratings of emotion expression correspond to "expert" ratings using the Specific Affect Coding System (SPAFF). The unique advantages of naive coding of emotion expression in marital interaction are discussed.

  17. Reading Others’ Emotions: The Role of Intuitive Judgments in Predicting Marital Satisfaction, Quality, and Stability

    Science.gov (United States)

    Waldinger, Robert J.; Hauser, Stuart T.; Schulz, Marc S.; Allen, Joseph P.; Crowell, Judith A.

    2006-01-01

    This study examined links between emotion expression in couple interactions and marital quality and stability. Core aspects of emotion expression in marital interactions were identified with the use of naïve observational coding by multiple raters. Judges rated 47 marital discussions with 15 emotion descriptors. Coders’ pooled ratings yielded good reliability on 4 types of emotion expression: hostility, distress, empathy, and affection. These 4 types were linked with concurrent marital satisfaction and interviewer ratings of marital adjustment as well as with marital stability at a 5-year follow-up. The study also examined the extent to which naïve judges’ ratings of emotion expression correspond to “expert” ratings using the Specific Affect Coding System (SPAFF). The unique advantages of naïve coding of emotion expression in marital interaction are discussed. PMID:14992610

  18. Fragmentation and stability of circadian activity rhythms predict mortality : the rotterdam study

    NARCIS (Netherlands)

    Zuurbier, Lisette A; Luik, Annemarie I; Hofman, Albert; Franco, Oscar H; Van Someren, Eus J W; Tiemeier, Henning

    2015-01-01

    Circadian rhythms and sleep patterns change as people age. Little is known about the associations between circadian rhythms and mortality rates. We investigated whether 24-hour activity rhythms and sleep characteristics independently predicted mortality. Actigraphy was used to determine the

  19. Multigene expression profile for predicting efficacy of cisplatin and vinorelbine in non-small cell lung cancer

    DEFF Research Database (Denmark)

    Buhl, I. K.; Christensen, I. J.; Santoni-Rugiu, E.

    2016-01-01

    Background: There is a need for biomarkers to predict efficacy of adjuvant chemotherapy in resected non-small cell lung cancer (NSCLC). Presented is a combined cisplatin and vinorelbine marker from a previously validated model system [1] tested in two cohorts. Methods: The profiles consist...... of correlated in vitro cytotoxicity of cisplatin and vinorelbine and mRNA expressions. Then each profile is correlated to mRNA expression of 3500 tumors. The cohorts are 1) a publically available dataset with 133 completely resected stage Ib-II NSCLC patients, 71 of whom received adjuvant cisplatin...... and vinorelbine (ACT) and 62 patients who had no adjuvant treatment (OBS) [2] and 2) 95 stage Ib-IIIb completely resected NSCLC patients who all received adjuvant cisplatin and vinorelbine [3]. Endpoint is cancer specific survival. Results: The combined cisplatin and vinorelbine profiles scored as a continuous...

  20. Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

    Science.gov (United States)

    Cirenajwis, Helena; Ekedahl, Henrik; Lauss, Martin; Harbst, Katja; Carneiro, Ana; Enoksson, Jens; Rosengren, Frida; Werner-Hartman, Linda; Törngren, Therese; Kvist, Anders; Fredlund, Erik; Bendahl, Pär-Ola; Jirström, Karin; Lundgren, Lotta; Howlin, Jillian; Borg, Åke; Gruvberger-Saal, Sofia K; Saal, Lao H; Nielsen, Kari; Ringnér, Markus; Tsao, Hensin; Olsson, Håkan; Ingvar, Christian; Staaf, Johan; Jönsson, Göran

    2015-05-20

    Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

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

    Directory of Open Access Journals (Sweden)

    Ji Soo Choi

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

  2. Cathode design investigation based on iterative correction of predicted profile errors in electrochemical machining of compressor blades

    Directory of Open Access Journals (Sweden)

    Zhu Dong

    2016-08-01

    Full Text Available Electrochemical machining (ECM is an effective and economical manufacturing method for machining hard-to-cut metal materials that are often used in the aerospace field. Cathode design is very complicated in ECM and is a core problem influencing machining accuracy, especially for complex profiles such as compressor blades in aero engines. A new cathode design method based on iterative correction of predicted profile errors in blade ECM is proposed in this paper. A mathematical model is first built according to the ECM shaping law, and a simulation is then carried out using ANSYS software. A dynamic forming process is obtained and machining gap distributions at different stages are analyzed. Additionally, the simulation deviation between the prediction profile and model is improved by the new method through correcting the initial cathode profile. Furthermore, validation experiments are conducted using cathodes designed before and after the simulation correction. Machining accuracy for the optimal cathode is improved markedly compared with that for the initial cathode. The experimental results illustrate the suitability of the new method and that it can also be applied to other complex engine components such as diffusers.

  3. The Temporal Stability and Predictive Ability of the Gambling Outcome Expectancies Scale (GOES): A Prospective Study.

    Science.gov (United States)

    Flack, Mal; Morris, Mary

    2016-09-01

    Previous research using the Gambling Outcome Expectancies Scale (GOES; Flack and Morris in J Gambl Stud, 2015. doi: 10.1007/s10899-014-9484-z ) revealed the instrument has excellent psychometric properties and differentially predicts gambling frequency and problem gambling scores. However, like the existing gambling motivation scales, the GOES psychometric properties and predictive utility have not been tested outside of cross sectional studies. The current study used a prospective survey design to redress this issue. Eight hundred and ninety-three participants, drawn from the general community, completed the second wave of the gambling survey. Temporal invariance testing revealed the GOES was reliable. Furthermore, the ability of the GOES to predict gambling behaviour using baseline and concurrent measures of gambling outcome expectancies was demonstrated. Specifically, consistent with the Wave 1 results, the gambling outcome expectancies that reflect diverse reasons for gambling (e.g., social, escape, and money) preferentially predicted gambling frequency whereas the narrower range of emotion focused reasons (e.g., excitement, escape, and ego enhancement) predicted gambling problems. Considered in light of the Wave 1 findings, these results underscore the need for gambling harm minimisation initiatives to take into account the emotion-oriented reasons for gambling.

  4. Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

    Science.gov (United States)

    Mathew, J.; Moat, R. J.; Paddea, S.; Francis, J. A.; Fitzpatrick, M. E.; Bouchard, P. J.

    2017-10-01

    Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of `innate scatter' and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated.

  5. Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

    Science.gov (United States)

    Mathew, J.; Moat, R. J.; Paddea, S.; Francis, J. A.; Fitzpatrick, M. E.; Bouchard, P. J.

    2017-12-01

    Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of `innate scatter' and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated.

  6. Transient stability enhancement of modern power grid using predictive Wide-Area Monitoring and Control

    Science.gov (United States)

    Yousefian, Reza

    This dissertation presents a real-time Wide-Area Control (WAC) designed based on artificial intelligence for large scale modern power systems transient stability enhancement. The WAC using the measurements available from Phasor Measurement Units (PMUs) at generator buses, monitors the global oscillations in the system and optimally augments the local excitation system of the synchronous generators. The complexity of the power system stability problem along with uncertainties and nonlinearities makes the conventional modeling non-practical or inaccurate. In this work Reinforcement Learning (RL) algorithm on the benchmark of Neural Networks (NNs) is used to map the nonlinearities of the system in real-time. This method different from both the centralized and the decentralized control schemes, employs a number of semi-autonomous agents to collaborate with each other to perform optimal control theory well-suited for WAC applications. Also, to handle the delays in Wide-Area Monitoring (WAM) and adapt the RL toward the robust control design, Temporal Difference (TD) is proposed as a solver for RL problem or optimal cost function. However, the main drawback of such WAC design is that it is challenging to determine if an offline trained network is valid to assess the stability of the power system once the system is evolved to a different operating state or network topology. In order to address the generality issue of NNs, a value priority scheme is proposed in this work to design a hybrid linear and nonlinear controllers. The algorithm so-called supervised RL is based on mixture of experts, where it is initialized by linear controller and as the performance and identification of the RL controller improves in real-time switches to the other controller. This work also focuses on transient stability and develops Lyapunov energy functions for synchronous generators to monitor the stability stress of the system. Using such energies as a cost function guarantees the convergence

  7. Evaluation of microwave oven heating for prediction of drug-excipient compatibilities and accelerated stability studies.

    Science.gov (United States)

    Schou-Pedersen, Anne Marie V; Østergaard, Jesper; Cornett, Claus; Hansen, Steen Honoré

    2015-05-15

    Microwave ovens have been used extensively in organic synthesis in order to accelerate reaction rates. Here, a set up comprising a microwave oven combined with silicon carbide (SiC) plates for the controlled microwave heating of model formulations has been applied in order to investigate, if a microwave oven is applicable for accelerated drug stability testing. Chemical interactions were investigated in three selected model formulations of drug and excipients regarding the formation of ester and amide reaction products. In the accelerated stability studies, a design of experiments (DoE) approach was applied in order to be able to rank excipients regarding reactivity: Study A: cetirizine with PEG 400, sorbitol, glycerol and propylene glycol. Study B: 6-aminocaproic acid with citrate, acetate, tartrate and gluconate. Study C: atenolol with citric, tartaric, malic, glutaric, and sorbic acid. The model formulations were representative for oral solutions (co-solvents), parenteral solutions (buffer species) and solid dosage forms (organic acids applicable for solubility enhancement). The DoE studies showed overall that the same impurities were generated by microwave oven heating leading to temperatures between 150°C and 180°C as compared to accelerated stability studies performed at 40°C and 80°C using a conventional oven. Ranking of the reactivity of the excipients could be made in the DoE studies performed at 150-180°C, which was representative for the ranking obtained after storage at 40°C and 80°C. It was possible to reduce the time needed for drug-excipient compatibility testing of the three model formulations from weeks to less than an hour in the three case studies. The microwave oven is therefore considered to be an interesting alternative to conventional thermal techniques for the investigation of drug-excipient interactions during preformulation. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. 3D Microstructure Effects in Ni-YSZ Anodes: Prediction of Effective Transport Properties and Optimization of Redox Stability

    Directory of Open Access Journals (Sweden)

    Omar M. Pecho

    2015-08-01

    Full Text Available This study investigates the influence of microstructure on the effective ionic and electrical conductivities of Ni-YSZ (yttria-stabilized zirconia anodes. Fine, medium, and coarse microstructures are exposed to redox cycling at 950 °C. FIB (focused ion beam-tomography and image analysis are used to quantify the effective (connected volume fraction (Φeff, constriction factor (β, and tortuosity (τ. The effective conductivity (σeff is described as the product of intrinsic conductivity (σ0 and the so-called microstructure-factor (M: σeff = σ0*M. Two different methods are used to evaluate the M-factor: (1 by prediction using a recently established relationship, Mpred = εβ0.36/τ5.17, and (2 by numerical simulation that provides conductivity, from which the simulated M-factor can be deduced (Msim. Both methods give complementary and consistent information about the effective transport properties and the redox degradation mechanism. The initial microstructure has a strong influence on effective conductivities and their degradation. Finer anodes have higher initial conductivities but undergo more intensive Ni coarsening. Coarser anodes have a more stable Ni phase but exhibit lower YSZ stability due to lower sintering activity. Consequently, in order to improve redox stability, it is proposed to use mixtures of fine and coarse powders in different proportions for functional anode and current collector layers.

  9. Direct drive ablation front stability: numerical predictions against flame front model

    Energy Technology Data Exchange (ETDEWEB)

    Masse, L. [Phd Student at IRPHE St Jerome, 13 - Marseille (France)]|[CEA/DAM-Ile de France, 91 - Bruyeres Le Chatel (France); Hallo, L.; Tallot, C. [CEA/DAM-Ile de France, 91 - Bruyeres Le Chatel (France)

    2000-07-01

    We study the linear stability of flows resulting from constant heating of planar targets by a laser. In the coordinate system of the ablation front there is a flow from the cold to hot region, which is situated in a gravity field oriented from hot to cold region. Similar types of flow can be observed in combustion systems, which involve propagation of flame fronts. A spectral model which studies linear perturbation is directly taken from the combustion community. Here we present the results for state as well as perturbed flows. Growth rate determined from the models are compared to each other, and preliminary numerical results from FC12 simulations are shown. (authors)

  10. Latent profiles of non-residential father engagement six years after divorce predict long term offspring outcomes

    Science.gov (United States)

    Modecki, Kathryn Lynn; Hagan, Melissa; Sandler, Irwin; Wolchik, Sharlene

    2014-01-01

    This study examined profiles of non-residential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) six to eight years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, nine years later. Parental divorce occurred during late childhood to early adolescence; indicators of non-residential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed nine years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes nine years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother’s remarriage, mother’s income, and gender, age and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems nine years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long-term. Implications of findings for policy and intervention are discussed. PMID:24484456

  11. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

    Directory of Open Access Journals (Sweden)

    Lund Ole

    2007-07-01

    Full Text Available Abstract Background Antigen presenting cells (APCs sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC and three mouse H2-IA alleles. Results The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR, we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. Conclusion

  12. An Experimental Evaluation of Generalized Predictive Control for Tiltrotor Aeroelastic Stability Augmentation in Airplane Mode of Flight

    Science.gov (United States)

    Kvaternik, Raymond G.; Piatak, David J.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of Generalized Predictive Control (GPC) for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in the airplane mode of flight are presented. GPC is an adaptive time-domain predictive control method that uses a linear difference equation to describe the input-output relationship of the system and to design the controller. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 that was modified to incorporate a GPC-based multi-input multi-output control algorithm to individually control each of the three swashplate actuators. Wing responses were used for feedback. The GPC-based control system was highly effective in increasing the stability of the critical wing mode for all of the conditions tested, without measurable degradation of the damping in the other modes. The algorithm was also robust with respect to its performance in adjusting to rapid changes in both the rotor speed and the tunnel airspeed.

  13. Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms.

    Science.gov (United States)

    Fayet, Guillaume; Rotureau, Patricia; Joubert, Laurent; Adamo, Carlo

    2011-10-01

    The molecular structures of 77 nitroaromatic compounds have been correlated to their thermal stabilities by combining the quantitative structure-property relationship (QSPR) method with density functional theory (DFT). More than 300 descriptors (constitutional, topological, geometrical and quantum chemical) have been calculated, and multilinear regressions have been performed to find accurate quantitative relationships with experimental heats of decomposition (-ΔH). In particular, this work demonstrates the importance of accounting for chemical mechanisms during the selection of an adequate experimental data set. A reliable QSPR model that presents a strong correlation with experimental data for both the training and the validation molecular sets (R (2) = 0.90 and 0.84, respectively) was developed for non-ortho-substituted nitroaromatic compounds. Moreover, its applicability domain was determined, and the model's predictivity reached 0.86 within this applicability domain. To our knowledge, this work has produced the first QSPR model, developed according to the OECD principles of regulatory acceptability, for predicting the thermal stabilities of energetic compounds.

  14. Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

    Directory of Open Access Journals (Sweden)

    Nina Melzer

    Full Text Available In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach. To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317 SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype.

  15. Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

    Science.gov (United States)

    Suzuki-Ohno, Yukari; Inoue, Maki N; Ohno, Kazunori

    2010-07-21

    We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density. (c) 2010 Elsevier Ltd. All rights reserved.

  16. Coconut oil predicts a beneficial lipid profile in pre-menopausal women in the Philippines

    OpenAIRE

    Feranil, Alan B.; Duazo, Paulita L.; Kuzawa, Christopher W.; Adair, Linda S.

    2011-01-01

    Coconut oil is a common edible oil in many countries, and there is mixed evidence for its effects on lipid profiles and cardiovascular disease risk. Here we examine the association between coconut oil consumption and lipid profiles in a cohort of 1,839 Filipino women (age 35–69 years) participating in the Cebu Longitudinal Health and Nutrition Survey, a community based study in Metropolitan Cebu City. Coconut oil intake was measured as individual coconut oil intake calculated using two 24-hou...

  17. A method to predict geomechanical properties and model well stability in horizontal boreholes

    Energy Technology Data Exchange (ETDEWEB)

    Gentzis, Thomas [Petron Resources, L.P., 3000 Internet Boulevard, Suite 400, Frisco, TX 75034 (United States); Deisman, Nathan; Chalaturnyk, Richard J. [Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB (Canada)

    2009-04-01

    A methodology is proposed to quickly assess the stability risk for horizontal wells drilled in coal seams. The first task involves the estimation of strength and deformation parameters of the coal by indirect methods, such as the use of core description to assign a Geological Strength Index (Gi). The second task involves the use of a finite element analysis called FLAC to investigate factors such as the depth of fluid penetration while drilling the horizontal well and the stability of the wellbore during simulated production. These two factors are important because coal fines generated by the drill bit action are carried by the drilling fluid into the cleat system of the coal, thereby plugging the permeability pathways, and causing formation damage. On the other hand, a wellbore that may become unstable during pressure drawdown would require a perforated or slotted production liner. In this study, the conditions of drilling and production necessary for a stable horizontal well drilled into a Mannville coal seam at 750-800 m in the central Alberta Plains, were studied. Modeling showed that the depth of fluid penetration would be at least 2.2 m if there is no filter cake formation while drilling underbalanced. Drilling fluid penetration would be minimal if a filter cake is formed under overbalanced conditions. Furthermore, FLAC analysis showed that drilling a smaller diameter hole (5 cm) would be preferable because this size results in a stable wellbore during production compared to the standard 15-cm diameter hole. (author)

  18. Stability evaluation of the rod in triangular array predicted by CFD

    Science.gov (United States)

    Upnere, S.; Jekabsons, N.

    2017-10-01

    Stability boundaries of structures consisting of circular cylinder arrays in the cross-flow are different from case to case depending on geometrical and mechanical variations of the rod bundle layout as well as depending on nature of the flow field, requiring an individual set of experiments for each characteristic case. In this study, close-packed staggered rod bundle with a pitch-to-diameter ratio of 1.1 is analysed. Numerical modelling has been done to check the stability threshold (critical velocity) of a flexibly mounted rod in an otherwise fixed rods array. The computational domain consists of the rod array with 6 rows of five cylinders. The unsteady flow through triangular cylinder array has been simulated using two-dimensional URANS computations with an open source Computational Fluid Dynamics (CFD) code. The CFD calculations are coupled with the six degree-of-freedom rigid body motion solver with reduced degree-of-freedom. Results were compared with the analytically determined threshold values.

  19. The hierarchy of stability and predictability in orthognathic surgery with rigid fixation: an update and extension

    Directory of Open Access Journals (Sweden)

    Phillips Ceib

    2007-04-01

    Full Text Available Abstract A hierarchy of stability exists among the types of surgical movements that are possible with orthognathic surgery. This report updates the hierarchy, focusing on comparison of the stability of procedures when rigid fixation is used. Two procedures not previously placed in the hierarchy now are included: correction of asymmetry is stable with rigid fixation and repositioning of the chin also is very stable. During the first post-surgical year, surgical movements in patients treated for Class II/long face problems tend to be more stable than those treated for Class III problems. Clinically relevant changes (more than 2 mm occur in a surprisingly large percentage of orthognathic surgery patients from one to five years post-treatment, after surgical healing is complete. During the first post-surgical year, patients treated for Class II/long face problems are more stable than those treated for Class III problems; from one to five years post-treatment, some patients in both groups experience skeletal change, but the Class III patients then are more stable than the Class II/long face patients. Fewer patients exhibit long-term changes in the dental occlusion than skeletal changes, because the dentition usually adapts to the skeletal change.

  20. Stability predictions for high-order ΣΔ modulators based on quasilinear modeling

    DEFF Research Database (Denmark)

    Risbo, Lars

    1994-01-01

    This paper introduces a novel interpretation of the instability mechanisms in high-order one-bit Sigma-Delta modulators. Furthermore, it is demonstrated how the maximum stable amplitude range can be predicted very well. The results are obtained using an extension of the well known quasilinear...

  1. Towards Adaptive Educational Assessments: Predicting Student Performance using Temporal Stability and Data Analytics in Learning Management Systems

    Energy Technology Data Exchange (ETDEWEB)

    Thakur, Gautam [ORNL; Olama, Mohammed M [ORNL; McNair, Wade [ORNL; Sukumar, Sreenivas R [ORNL

    2014-01-01

    Data-driven assessments and adaptive feedback are becoming a cornerstone research in educational data analytics and involve developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the students and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present our efforts in using data analytics that enable educationists to design novel data-driven assessment and feedback mechanisms. In order to achieve this objective, we investigate temporal stability of students grades and perform predictive analytics on academic data collected from 2009 through 2013 in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for assessments and predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total Grade Point Average(GPA) at the same term they enrolled in the course. Second, time series models in both frequency and time domains are applied to characterize the progression as well as overall projections of the grades. In particular, the model analyzed the stability as well as fluctuation of grades among students during the collegiate years (from freshman to senior) and disciplines. Third, Logistic Regression and Neural Network predictive models are used to identify students as early as possible who are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. The time series analysis indicates that assessments and continuous feedback are critical for freshman and sophomores (even with easy courses) than for seniors, and those assessments may be

  2. Early childhood profiles of sleep problems and self-regulation predict later school adjustment.

    Science.gov (United States)

    Williams, Kate E; Nicholson, Jan M; Walker, Sue; Berthelsen, Donna

    2016-06-01

    Children's sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. This study explores the normative developmental pathway for sleep problems and self-regulation across early childhood and investigates whether departure from the normative pathway is associated with later social-emotional adjustment to school. This study involved 2,880 children participating in the Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) - Infant Cohort from Wave 1 (0-1 years) to Wave 4 (6-7 years). Mothers reported on children's sleep problems, emotional, and attentional self-regulation at three time points from birth to 5 years. Teachers reported on children's social-emotional adjustment to school at 6-7 years. Latent profile analysis was used to establish person-centred longitudinal profiles. Three profiles were found. The normative profile (69%) had consistently average or higher emotional and attentional regulation scores and sleep problems that steadily reduced from birth to 5 years. The remaining 31% of children were members of two non-normative self-regulation profiles, both characterized by escalating sleep problems across early childhood and below mean self-regulation. Non-normative group membership was associated with higher teacher-reported hyperactivity and emotional problems, and poorer classroom self-regulation and prosocial skills. Early childhood profiles of self-regulation that include sleep problems offer a way to identify children at risk of poor school adjustment. Children with escalating early childhood sleep problems should be considered an important target group for school transition interventions. © 2016 The British Psychological Society.

  3. Draft forces prediction model for standard single tines by using principles of soil mechanics and soil profile evaluation

    Directory of Open Access Journals (Sweden)

    Amer Khalid Ahmed Al-Neama

    2017-06-01

    Full Text Available This paper explains a model to predict the draft force acting on varying standard single tines by using principles of soil mechanics and soil profile evaluation. Draft force (Fd measurements were made with four standard single tines comprising Heavy Duty, Double Heart, Double Heart with Wings and Duck Foot. Tine widths were 6.5, 13.5, 45 and 40 cm, respectively. The test was conducted in a soil bin with sandy loam soil. The effects of forward speeds and working depths on draft forces were investigated under controlled lab conditions. Results were evaluated based on a prediction model. A good correlation between measured and predicted Fd values for all tines with an average absolute variation less than 15 % was found.

  4. Prediction of Combustion Stability and Flashback in Turbines with High-Hydrogen Fuel

    Energy Technology Data Exchange (ETDEWEB)

    Lieuwen, Tim [Georgia Inst. of Technology, Atlanta, GA (United States); Santavicca, Dom [Georgia Inst. of Technology, Atlanta, GA (United States); Yang, Vigor [Georgia Inst. of Technology, Atlanta, GA (United States)

    2012-03-31

    During the duration of this sponsorship, we broadened our understanding of combustion instabilities through both analytical and experimental work. Predictive models were developed for flame response to transverse acoustic instabilities and for quantifying how a turbulent flame responds to velocity and fuel/air ratio forcing. Analysis was performed on the key instability mechanisms controlling heat release response for flames over a wide range of instability frequencies. Importantly, work was done closely with industrial partners to transition existing models into internal instability prediction codes. Experimentally, the forced response of hydrogen-enriched natural gas/air premixed and partially premixed flames were measured. The response of a lean premixed flame was investigated, subjected to velocity, equivalence ratio, and both forcing mechanisms simultaneously. In addition, important physical mechanisms controlling the response of partially premixed flames to inlet velocity and equivalence ratio oscillations were analyzed. This final technical report summarizes our findings and major publications stemming from this program.

  5. Murine Cyp3a knockout chimeric mice with humanized liver: prediction of the metabolic profile of nefazodone in humans.

    Science.gov (United States)

    Nakada, Naoyuki; Kawamura, Akio; Kamimura, Hidetaka; Sato, Koya; Kazuki, Yasuhiro; Kakuni, Masakazu; Ohbuchi, Masato; Kato, Kota; Tateno, Chise; Oshimura, Mitsuo; Usui, Takashi

    2016-01-01

    Chimeric mice with humanized livers (PXB mice) are used to investigate the metabolism and pharmacokinetics of drugs in humans. However, residual murine enzymatic activities derived from the liver and the presence of mouse small intestinal metabolism can hamper the prediction of human drug metabolism. Recently murine Cytochrome P450 3a gene knockout chimeric mice with humanized livers (Cyp3a KO CM) were developed. To evaluate the prediction of drug metabolism, nefazodone (NEF) was administered orally at 10 mg/kg to the following mouse strains: Cyp3a KO CM, murine Cyp3a gene knockout (Cyp3a KO), PXB and severe combined immunodeficiency (SCID) mice. Liquid chromatography-mass spectrometry was used for metabolic profiling of plasma, urine and bile. The prediction of human metabolite levels such as hydroxy nefazodone (OH-NEF), triazoledione form (TD), m-chlorophenylpiperazine and dealkyl metabolites in Cyp3a KO CM was superior to that in Cyp3a KO, PXB or SCID mice. Further, clinical exposure levels of NEF, OH-NEF and TD were reproduced in Cyp3a KO CM. In contrast, NEF was rapidly metabolized to TD in both PXB and SCID mice but not in Cyp3a KO mice, suggesting that murine CYP3A is involved in the elimination of NEF in these mice. These findings demonstrate that the metabolic profile of NEF in Cyp3a KO CM differs qualitatively and quantitatively from that in PXB mice due to the higher metabolic rate of NEF and its metabolites via murine CYP3A. Therefore Cyp3a KO CM might be useful in predicting the metabolic profiles of drug candidates in humans. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.

    Directory of Open Access Journals (Sweden)

    Kosuke Yoshihara

    Full Text Available BACKGROUND: Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer. METHODOLOGY/PRINCIPAL FINDINGS: Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01 and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR, 3.72; 95% confidence interval (CI, 2.66-5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20-1.98; p = 0.0008. Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008. CONCLUSIONS/SIGNIFICANCE: The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.

  7. Predictability and stability of laser-assisted subepithelial keratectomy with mitomycin C for the correction of high myopia.

    Science.gov (United States)

    Iu, Lawrence P L; Fan, Michelle C Y; Chen, Ivan N; Lai, Jimmy S M

    2017-06-01

    The purpose of this study was to evaluate the predictability and stability of laser-assisted subepithelial keratectomy (LASEK) with mitomycin C (MMC) in correction of high myopia (≤-6.0 diopters [D]) as compared to low-to-moderate myopia (>-6.0 D).This is a retrospective, comparative, cohort study which included 43 eyes of 43 consecutive patients who underwent LASEK with MMC in a private hospital in Hong Kong by a single surgeon. Twenty-five eyes had high myopia (mean spherical equivalent [SE] = -8.53 ± 1.82 D) and 18 eyes had low-to-moderate myopia (mean SE = -3.99 ± 1.37 D) before surgery.In terms of refractive predictability, mean SE was significantly better in eyes with preoperative low-to-moderate myopia than high myopia at 6 months (0.04 ± 0.23 vs 0.31 ± 0.52 D, P = .035). In terms of refractive stability, between 1 and 3 months, both groups had mean absolute change of SE of around 0.25 D. Between 3 and 6 months, preoperative low-to-moderate myopia group had significantly less absolute change of SE compared to high myopia group (0.07 vs 0.23 D, P = .003). More eyes with preoperative high myopia changed SE by more than 0.25 D than those with low-to-moderate myopia between 3 and 6 months (32.0% vs 5.6%, P = .057).In conclusion, LASEK with MMC is more unpredictable and unstable in correction of high myopia than low-to-moderate myopia. The refractive outcome of most low-to-moderate myopia correction stabilizes at 3 months. Stability is not achieved until after 6 months in high myopia correction.

  8. Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

    Science.gov (United States)

    Padfield, G. D.; Duval, R. K.

    1982-01-01

    A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

  9. Surface profile gradient in amorphous Ta{sub 2}O{sub 5} semi conductive layers regulates nanoscale electric current stability

    Energy Technology Data Exchange (ETDEWEB)

    Cefalas, A.C., E-mail: ccefalas@eie.gr [National Hellenic Research Foundation, Theoretical and Physical Chemistry Institute, 48 Vassileos Constantinou Avenue, Athens 11635 (Greece); Kollia, Z.; Spyropoulos-Antonakakis, N.; Gavriil, V. [National Hellenic Research Foundation, Theoretical and Physical Chemistry Institute, 48 Vassileos Constantinou Avenue, Athens 11635 (Greece); Christofilos, D.; Kourouklis, G. [Physics Division, School of Technology, Aristotle University of Thessaloniki, Thessaloniki 54124 (Greece); Semashko, V.V.; Pavlov, V. [Kazan Federal University, Institute of Physics, 18 Kremljovskaja str., Kazan 420008 (Russian Federation); Sarantopoulou, E. [National Hellenic Research Foundation, Theoretical and Physical Chemistry Institute, 48 Vassileos Constantinou Avenue, Athens 11635 (Greece); Kazan Federal University, Institute of Physics, 18 Kremljovskaja str., Kazan 420008 (Russian Federation)

    2017-02-28

    Highlights: • The work links the surface morphology of amorphous semiconductors with both their electric-thermal properties and current stability at the nanoscale (<1 μm). • Measured high correlation value between surface morphological spatial gradient and conductive electron energy spatial gradient or thermal gradient. • Unidirectional current stability is associated with asymmetric nanodomains along nanosize conductive paths. • Bidirectional current stability is inherent with either long conductive paths or nanosize conductive paths along symmetric nanodomains. • Conclusion: Surface design improves current stability across nanoelectonic junctions. - Abstract: A link between the morphological characteristics and the electric properties of amorphous layers is established by means of atomic, conductive, electrostatic force and thermal scanning microscopy. Using amorphous Ta{sub 2}O{sub 5} (a-Ta{sub 2}O{sub 5}) semiconductive layer, it is found that surface profile gradients (morphological gradient), are highly correlated to both the electron energy gradient of trapped electrons in interactive Coulombic sites and the thermal gradient along conductive paths and thus thermal and electric properties are correlated with surface morphology at the nanoscale. Furthermore, morphological and electron energy gradients along opposite conductive paths of electrons intrinsically impose a current stability anisotropy. For either long conductive paths (L > 1 μm) or along symmetric nanodomains, current stability for both positive and negative currents i is demonstrated. On the contrary, for short conductive paths along non-symmetric nanodomains, the set of independent variables (L, i) is spanned by two current stability/intability loci. One locus specifies a stable state for negative currents, while the other locus also describes a stable state for positive currents.

  10. Evaluating the Stability of RNA-Seq Transcriptome Profiles and Drug-Induced Immune-Related Expression Changes in Whole Blood.

    Directory of Open Access Journals (Sweden)

    John F Bowyer

    Full Text Available Methods were developed to evaluate the stability of rat whole blood expression obtained from RNA sequencing (RNA-seq and assess changes in whole blood transcriptome profiles in experiments replicated over time. Expression was measured in globin-depleted RNA extracted from the whole blood of Sprague-Dawley rats, given either saline (control or neurotoxic doses of amphetamine (AMPH. The experiment was repeated four times (paired control and AMPH groups over a 2-year span. The transcriptome of the control and AMPH-treated groups was evaluated on: 1 transcript levels for ribosomal protein subunits; 2 relative expression of immune-related genes; 3 stability of the control transcriptome over 2 years; and 4 stability of the effects of AMPH on immune-related genes over 2 years. All, except one, of the 70 genes that encode the 80s ribosome had levels that ranked in the top 5% of all mean expression levels. Deviations in sequencing performance led to significant changes in the ribosomal transcripts. The overall expression profile of immune-related genes and genes specific to monocytes, T-cells or B-cells were well represented and consistent within treatment groups. There were no differences between the levels of ribosomal transcripts in time-matched control and AMPH groups but significant differences in the expression of immune-related genes between control and AMPH groups. AMPH significantly increased expression of some genes related to monocytes but down-regulated those specific to T-cells. These changes were partially due to changes in the two types of leukocytes present in blood, which indicate an activation of the innate immune system by AMPH. Thus, the stability of RNA-seq whole blood transcriptome can be verified by assessing ribosomal protein subunits and immune-related gene expression. Such stability enables the pooling of samples from replicate experiments to carry out differential expression analysis with acceptable power.

  11. Electrochemical Investigations of 4-Methoxypyridine Adsorption on Au(111) Predict Its Suitability for Stabilizing Au Nanoparticles.

    Science.gov (United States)

    Unni, Bipinlal; Simon, Sajna; Burgess, Ian J

    2015-09-15

    A thermodynamic analysis of the adsorption of 4-methoxypyridine (MOP) on Au(111) surfaces is presented in an effort to determine its propensity to stabilize metal nanoparticles. The adsorption of MOP is compared and contrasted to the adsorption of 4-dimethylaminopyridine (DMAP), the latter of which is well-known to form stable Au nanoparticles. Electrochemical studies show that MOP, like most pyridine derivatives, can exhibit two different adsorption states. The electrical state of the metal, the pH of the solution, and the surface crystallography determine whether MOP adopts a low-coverage, π-bonded orientation or a high-coverage, σ-type orientation. A modified Langmuir adsorption isotherm is used to extract free energies of adsorption which are roughly 10% stronger for DMAP compared to MOP at equivalent conditions when expressed on a rational basis. The higher adsorption strength is attributed to DMAP's greater Lewis basicity. Qualitatively, MOP and DMAP adsorption are found to be completely analogous, implying that MOP-protected gold particles should be stable under conditions that favor the high-coverage adsorption state. Using a previously reported, single-phase synthesis, this is shown to be the case.

  12. Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.)

    DEFF Research Database (Denmark)

    Johansson, Gine Ørnholt; Frosch, Stina; Gudjónsdóttir, María

    2017-01-01

    industry can improve the yield. Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture...

  13. Predicting lower third molar eruption on panoramic radiographs after cephalometric comparison of profile and panoramic radiographs

    DEFF Research Database (Denmark)

    Begtrup, Anders; Grønastøð, Halldis Á; Christensen, Ib Jarle

    2012-01-01

    ), with no known diseases. Cephalometric measurements on panoramic and profile radiographs were performed and compared, i.e. the size of the gonial angle and sagittal distance from the alveolar margin between the mandibular central incisors to the anterior border of the mandibular ramus. Furthermore...

  14. Early Childhood Profiles of Sleep Problems and Self-Regulation Predict Later School Adjustment

    Science.gov (United States)

    Williams, Kate E.; Nicholson, Jan M.; Walker, Sue; Berthelsen, Donna

    2016-01-01

    Background: Children's sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims: This study explores the normative developmental pathway for sleep problems and self-regulation…

  15. Profiles of Observed Infant Anger Predict Preschool Behavior Problems: Moderation by Life Stress

    Science.gov (United States)

    Brooker, Rebecca J.; Buss, Kristin A.; Lemery-Chalfant, Kathryn; Aksan, Nazan; Davidson, Richard J.; Goldsmith, H. Hill

    2014-01-01

    Using both traditional composites and novel profiles of anger, we examined associations between infant anger and preschool behavior problems in a large, longitudinal data set (N = 966). We also tested the role of life stress as a moderator of the link between early anger and the development of behavior problems. Although traditional measures of…

  16. Predictive Validity of Career Decision-Making Profiles over Time among Chinese College Students

    Science.gov (United States)

    Tian, Lin; Guan, Yanjun; Chen, Sylvia Xiaohua; Levin, Nimrod; Cai, Zijun; Chen, Pei; Zhu, Chengfeng; Fu, Ruchunyi; Wang, Yang; Zhang, Shu

    2014-01-01

    Two studies were conducted to validate the Chinese version of the Career Decision-Making Profiles (CDMP) questionnaire, a multidimensional measure of the way individuals make career decisions. Results of Study 1 showed that after dropping 1 item from the original CDMP scale, the 11-factor structure was supported among Chinese college students (N =…

  17. Simpler Evaluation of Predictions and Signature Stability for Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Yvonne E. Pittelkow

    2009-01-01

    Full Text Available Scientific advances are raising expectations that patient-tailored treatment will soon be available. The development of resulting clinical approaches needs to be based on well-designed experimental and observational procedures that provide data to which proper biostatistical analyses are applied. Gene expression microarray and related technology are rapidly evolving. It is providing extremely large gene expression profiles containing many thousands of measurements. Choosing a subset from these gene expression measurements to include in a gene expression signature is one of the many challenges needing to be met. Choice of this signature depends on many factors, including the selection of patients in the training set. So the reliability and reproducibility of the resultant prognostic gene signature needs to be evaluated, in such a way as to be relevant to the clinical setting. A relatively straightforward approach is based on cross validation, with separate selection of genes at each iteration to avoid selection bias. Within this approach we developed two different methods, one based on forward selection, the other on genes that were statistically significant in all training blocks of data. We demonstrate our approach to gene signature evaluation with a well-known breast cancer data set.

  18. Toward a complete theory for predicting inclusive deuteron breakup away from stability

    Energy Technology Data Exchange (ETDEWEB)

    Potel, G.; Li, W.; Rotureau, J. [Michigan State University, Facility for Rare Isotope Beams, East Lansing, MI (United States); Perdikakis, G. [Michigan State University, Facility for Rare Isotope Beams, East Lansing, MI (United States); Central Michigan University, Department of Physics, Mt. Pleasant, MI (United States); Center for the Evolution of the Elements, Joint Institute for Nuclear Astrophysics, East Lansing, MI (United States); Carlson, B.V. [DCTA, Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP (Brazil); Atkinson, M.C.; Dickhoff, W.H. [Washington University, Department of Physics, St. Louis, MO (United States); Escher, J.E. [Lawrence Livermore National Laboratory, Livermore, CA (United States); Hussein, M.S. [DCTA, Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP (Brazil); Universidade de Sao Paulo, Departamento de Fisica Matematica, Instituto de Fisica, Sao Paulo, SP (Brazil); Universidade de Sao Paulo, Instituto de Estudos Avancados, Sao Paulo, SP (Brazil); Lei, J.; Moro, A.M. [Universidad de Sevilla, Departamento de FAMN, Sevilla (Spain); Macchiavelli, A.O. [Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, CA (United States); Nunes, F.M. [Michigan State University, Facility for Rare Isotope Beams, East Lansing, MI (United States); Michigan State University, Department of Physics and Astronomy, East Lansing, MI (United States); Pain, S.D. [Oak Ridge National Laboratory, Physics Division, Oak Ridge, TN (United States)

    2017-09-15

    We present an account of the current status of the theoretical treatment of inclusive (d, p) reactions in the breakup-fusion formalism, pointing to some applications and making the connection with current experimental capabilities. Three independent implementations of the reaction formalism have been recently developed, making use of different numerical strategies. The codes also originally relied on two different but equivalent representations, namely the prior (Udagawa-Tamura, UT) and the post (Ichimura-Austern-Vincent, IAV) representations. The different implementations have been benchmarked for the first time, and then applied to the Ca isotopic chain. The neutron-Ca propagator is described in the Dispersive Optical Model (DOM) framework, and the interplay between elastic breakup (EB) and non-elastic breakup (NEB) is studied for three Ca isotopes at two different bombarding energies. The accuracy of the description of different reaction observables is assessed by comparing with experimental data of (d, p) on {sup 40,48}Ca. We discuss the predictions of the model for the extreme case of an isotope ({sup 60}Ca) currently unavailable experimentally, though possibly available in future facilities (nominally within production reach at FRIB). We explore the use of (d, p) reactions as surrogates for (n,γ) processes, by using the formalism to describe the compound nucleus formation in a (d,pγ) reaction as a function of excitation energy, spin, and parity. The subsequent decay is then computed within a Hauser-Feshbach formalism. Comparisons between the (d,pγ) and (n,γ) induced gamma decay spectra are discussed to inform efforts to infer neutron captures from (d,pγ) reactions. Finally, we identify areas of opportunity for future developments, and discuss a possible path toward a predictive reaction theory. (orig.)

  19. Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle.

    Science.gov (United States)

    Shi, Ke; Yuan, Xiaofang; Liu, Liang

    2018-01-01

    Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a novel model predictive controller-based multi-model control system (MPC-MMCS) is proposed to solve the longitudinal stability problem of DDEV. Firstly, the operation state of DDEV is summarized as three kinds of typical operating modes. A submodel set is established to accurately represent the state value of the corresponding operating mode. Secondly, the matching degree between the state of actual DDEV and each submodel is analyzed. The matching degree is expressed as the weight coefficient and calculated by a modified recursive Bayes theorem. Thirdly, a nonlinear MPC is designed to achieve the optimal wheel slip ratio for each submodel. The optimal design of MPC is realized by parallel chaos optimization algorithm(PCOA)with computational accuracy and efficiency. Finally, the control output of MPC-MMCS is computed by the weighted output of each MPC to achieve smooth switching between operating modes. The proposed MPC-MMCS is evaluated on eight degrees of freedom(8DOF)DDEV model simulation platform and simulation results of different condition show the benefits of the proposed control system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. SUMF1 mutations affecting stability and activity of formylglycine generating enzyme predict clinical outcome in multiple sulfatase deficiency.

    Science.gov (United States)

    Schlotawa, Lars; Ennemann, Eva Charlotte; Radhakrishnan, Karthikeyan; Schmidt, Bernhard; Chakrapani, Anupam; Christen, Hans-Jürgen; Moser, Hugo; Steinmann, Beat; Dierks, Thomas; Gärtner, Jutta

    2011-03-01

    Multiple Sulfatase Deficiency (MSD) is caused by mutations in the sulfatase-modifying factor 1 gene encoding the formylglycine-generating enzyme (FGE). FGE post translationally activates all newly synthesized sulfatases by generating the catalytic residue formylglycine. Impaired FGE function leads to reduced sulfatase activities. Patients display combined clinical symptoms of single sulfatase deficiencies. For ten MSD patients, we determined the clinical phenotype, FGE expression, localization and stability, as well as residual FGE and sulfatase activities. A neonatal, very severe clinical phenotype resulted from a combination of two nonsense mutations leading to almost fully abrogated FGE activity, highly unstable FGE protein and nearly undetectable sulfatase activities. A late infantile mild phenotype resulted from FGE G263V leading to unstable protein but high residual FGE activity. Other missense mutations resulted in a late infantile severe phenotype because of unstable protein with low residual FGE activity. Patients with identical mutations displayed comparable clinical phenotypes. These data confirm the hypothesis that the phenotypic outcome in MSD depends on both residual FGE activity as well as protein stability. Predicting the clinical course in case of molecularly characterized mutations seems feasible, which will be helpful for genetic counseling and developing therapeutic strategies aiming at enhancement of FGE. © 2011 Macmillan Publishers Limited All rights reserved 1018-4813/11

  1. Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

    National Research Council Canada - National Science Library

    Safoora Yousefi; Fatemeh Amrollahi; Mohamed Amgad; Chengliang Dong; Joshua E Lewis; Congzheng Song; David A Gutman; Sameer H Halani; Jose Enrique Velazquez Vega; Daniel J Brat; Lee A D Cooper

    2017-01-01

    .... In this paper, we demonstrate how deep learning and Bayesian optimization methods that have been remarkably successful in general high-dimensional prediction tasks can be adapted to the problem...

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

    Science.gov (United States)

    Lopez, Daniel; Pazos, Florencio

    2013-01-01

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

  3. Molecular Profiling Predicts the Existence of Two Functionally Distinct Classes of Ovarian Cancer Stroma

    OpenAIRE

    Lili, Loukia N.; Lilya V Matyunina; L DeEtte Walker; Benigno, Benedict B; John F. McDonald

    2013-01-01

    Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0) gene expression ...

  4. Taxonomic and predicted metabolic profiles of the human gut microbiome in pre-Columbian mummies.

    Science.gov (United States)

    Santiago-Rodriguez, Tasha M; Fornaciari, Gino; Luciani, Stefania; Dowd, Scot E; Toranzos, Gary A; Marota, Isolina; Cano, Raul J

    2016-11-01

    Characterization of naturally mummified human gut remains could potentially provide insights into the preservation and evolution of commensal and pathogenic microorganisms, and metabolic profiles. We characterized the gut microbiome of two pre-Columbian Andean mummies dating to the 10-15th centuries using 16S rRNA gene high-throughput sequencing and metagenomics, and compared them to a previously characterized gut microbiome of an 11th century AD pre-Columbian Andean mummy. Our previous study showed that the Clostridiales represented the majority of the bacterial communities in the mummified gut remains, but that other microbial communities were also preserved during the process of natural mummification, as shown with the metagenomics analyses. The gut microbiome of the other two mummies were mainly comprised by Clostridiales or Bacillales, as demonstrated with 16S rRNA gene amplicon sequencing, many of which are facultative anaerobes, possibly consistent with the process of natural mummification requiring low oxygen levels. Metagenome analyses showed the presence of other microbial groups that were positively or negatively correlated with specific metabolic profiles. The presence of sequences similar to both Trypanosoma cruzi and Leishmania donovani could suggest that these pathogens were prevalent in pre-Columbian individuals. Taxonomic and functional profiling of mummified human gut remains will aid in the understanding of the microbial ecology of the process of natural mummification. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Coconut oil predicts a beneficial lipid profile in pre-menopausal women in the Philippines

    Science.gov (United States)

    Feranil, Alan B.; Duazo, Paulita L.; Kuzawa, Christopher W.; Adair, Linda S.

    2011-01-01

    Coconut oil is a common edible oil in many countries, and there is mixed evidence for its effects on lipid profiles and cardiovascular disease risk. Here we examine the association between coconut oil consumption and lipid profiles in a cohort of 1,839 Filipino women (age 35–69 years) participating in the Cebu Longitudinal Health and Nutrition Survey, a community based study in Metropolitan Cebu City. Coconut oil intake was measured as individual coconut oil intake calculated using two 24-hour dietary recalls (9.54 ± 8.92 grams). Cholesterol profiles were measured in plasma samples collected after an overnight fast. Mean lipid values in this sample were total cholesterol (TC) (186.52 ± 38.86 mg/dL), high density lipoprotein cholesterol (HDL-c) (40.85 ± 10.30 mg/dL), low density lipoprotein cholesterol (LDL-c) (119.42 ± 33.21 mg/dL), triglycerides (130.75 ± 85.29 mg/dL) and the TC/HDL ratio (4.80 ± 1.41). Linear regression models were used to estimate the association between coconut oil intake and each plasma lipid outcome after adjusting for total energy intake, age, body mass index (BMI), number of pregnancies, education, menopausal status, household assets and urban residency. Dietary coconut oil intake was positively associated with HDL-c levels. PMID:21669587

  6. A novel model for predicting the temperature profile in gas lift wells

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Mahdiani

    2016-12-01

    Full Text Available One of the most common methods for calculating the production oil rate in a gas lift well is nodal analysis. This manner is an accurate one, but unfortunately it is very time consuming and slow. In some modern studies in petroleum engineering such as close loop control of the wells this slowness makes it impossible to have an online optimization. In fact, before the end of the optimization the input parameters have changed. Thus having a faster model is necessary specially in some of the new studies. One of the sources of slowness of the nodal analysis is the temperature profile estimation of the wells. There are two general approaches for temperature profile estimation, some like heat balance are accurate but slow. Others, similar to linear profile assumption are fast but inaccurate and usually are not used commonly. Here, as a new approach, a combination model of heat balance and linear temperature profile estimation has represented which makes the nodal analysis three times faster and it is as accurate as heat balance calculations. To create this, two points (gas injection point and end of tubing are selected, then using heat balance equations the temperature of those two points are calculated. In normal nodal analysis the temperature of each wanted point in the well is estimated by heat balance and it is the source of slowness but here just two points are calculated using those complex equations. It seems that between these points assuming a linear temperature profile is reasonable because the parameters of the well and production such as physical tubing, and casing shape and properties and gas oil ratio are constants. But of course, it still has some deviation from the complete method of heat balance which using regression and assigning a coefficient to the model even this much of the deviation could be overcame. Finally, the model was tested in various wells and it was compared with the normal nodal analysis with complete heat balance

  7. MicroRNA profile predicts recurrence after resection in patients with hepatocellular carcinoma within the Milan Criteria.

    Directory of Open Access Journals (Sweden)

    Fumiaki Sato

    Full Text Available OBJECTIVE: Hepatocellular carcinoma (HCC is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection. METHODS: We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out cross-validation method, and the time-averaged area under the ROC curve (ta-AUROC. RESULTS: The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs than in the tumor-derived microRNAs (T-miRs, P<0.0001. The best ta-AUROC using the whole dataset, T-miRs, N-miRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P = 0.00029. The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P<0.0001. This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the 'field effect'. CONCLUSION: MicroRNA profiling can predict HCC recurrence in Milan criteria cases.

  8. Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

    Directory of Open Access Journals (Sweden)

    Robert W Chapman

    Full Text Available Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis, a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs and supervised machine learning, collective changes in the expression of a limited suite of genes (233 representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold, with most individual transcripts making a small contribution (<1% to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

  9. Advances in refractive surgery: microkeratome and femtosecond laser flap creation in relation to safety, efficacy, predictability, and biomechanical stability.

    Science.gov (United States)

    Stonecipher, Karl; Ignacio, Teresa S; Stonecipher, Megan

    2006-08-01

    Methods of flap creation have changed over the years from the evolution of the mechanical microkeratome to the introduction of the IntraLase femtosecond laser keratome, both of which have different mechanisms of action to create corneal resections. Previous studies report the advantages and disadvantages of the mechanical microkeratome and the IntraLase femtosecond laser. The critical components in laser in-situ keratomileusis surgery remain the same, however: safety, efficiency, predictability, and biomechanical stability. Keratoectasia and flap efficiency remain a constant safety concern in laser in-situ keratomileusis surgery. Unexpectedly thick flaps as well as variable thickness continue to be a concern with safety in relation to microkeratome technology. Epithelial preservation, flap complications, and newer issues such as Transient Light Sensitivity Syndrome are safety concerns of flap creation. Improved outcomes with regards to vision, induced astigmatism, induced higher-order aberrations, and enhancement rates are seen to favor predictability of femtosecond technologies over the microkeratome. Recent biomechanical studies show improved healing with femtosecond laser flap creation compared with blade-assisted flap creation. The aim of this review is to summarize the key components for both the microkeratome and the femtosecond laser and to update on the recent advances reported on these topics.

  10. PREDICTION OF STABILITY AND THERMAL CONDUCTIVITY OF SnO2NANOFLUID VIA STATISTICAL METHOD AND AN ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    A. Kazemi-Beydokhti

    2015-12-01

    Full Text Available Abstract Central composite rotatable design (CCRD and artificial neural networks (ANN have been applied to optimize the performance of nanofluid systems. In this regard, the performance was evaluated by measuring the stability and thermal conductivity ratio based on the critical independent variables such as temperature, particle volume fraction and the pH of the solution. A total of 20 experiments were accomplished for the construction of second-order polynomial equations for both target outputs. All the influential factors, their mutual effects and their quadratic terms were statistically validated by analysis of variance (ANOVA. According to the results, the predicted values were in reasonable agreement with the experimental data as more than 96% and 95% of the variation could be predicted by the respective models for zeta potential and thermal conductivity ratio. Also, ANN proved to be a very promising method in comparison with CCD for the purpose of process simulation due to the complexity involved in generalization of the nanofluid system.

  11. Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library

    Directory of Open Access Journals (Sweden)

    Gisbert Schneider

    2011-09-01

    Full Text Available We present a self-organizing map (SOM approach to predicting macromolecular targets for combinatorial compound libraries. The aim was to study the usefulness of the SOM in combination with a topological pharmacophore representation (CATS for selecting biologically active compounds from a virtual combinatorial compound collection, taking the multi-component Biginelli dihydropyrimidine reaction as an example. We synthesized a candidate compound from this library, for which the SOM model suggested inhibitory activity against cyclin-dependent kinase 2 (CDK2 and other kinases. The prediction was confirmed in an in vitro panel assay comprising 48 human kinases. We conclude that the computational technique may be used for ligand-based in silico pharmacology studies, off-target prediction, and drug re-purposing, thereby complementing receptor-based approaches.

  12. A biomarker profile for predicting efficacy of cisplatin-vinorelbine therapy in malignant pleural mesothelioma

    DEFF Research Database (Denmark)

    Zimling, Zarah Glad; Sørensen, Jens Benn; Gerds, Thomas Alexander

    2012-01-01

    Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated with cispl......Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated...

  13. Effect of the fermentation pH on the storage stability of Lactobacillus rhamnosus preparations and suitability of in vitro analyses of cell physiological functions to predict it.

    Science.gov (United States)

    Saarela, M H; Alakomi, H-L; Puhakka, A; Mättö, J

    2009-04-01

    To investigate how cell physiological functions can predict the stability of freeze-dried probiotics. In addition, the effect of the fermentation pH on the stability of probiotics was investigated. Fermenter-grown (pH 5.8 or 5.0) Lactobacillus rhamnosus cells were freeze-dried and their survival was evaluated during storage at 37 degrees C, in apple juice and during acid [hydrochloric acid (HCl) and malic acid] and bile exposure. Cells grown at pH 5.0 were generally coping better with acid-stress than cells grown at pH 5.8. Cells were more sensitive to malic acid compared with HCl. Short-term stability results of Lact. rhamnosus cells in malic acid correlated well with the long-term stability results in apple juice, whereas the results of cell membrane integrity studies were in accordance with bile exposure results. Malic acid exposure can prove useful in evaluating the long-term stability of probiotic preparations in apple juice. Fermentation at reduced pH may ensure a better performance of Lact. rhamnosus cells during the subsequent acid-stress. The beneficial effect of lowered fermentation pH to Lact. rhamnosus stability during storage in apple juice and the usefulness of malic acid test in predicting the stability were shown.

  14. Prediction du profil de durete de l'acier AISI 4340 traite thermiquement au laser

    Science.gov (United States)

    Maamri, Ilyes

    Les traitements thermiques de surfaces sont des procedes qui visent a conferer au coeur et a la surface des pieces mecaniques des proprietes differentes. Ils permettent d'ameliorer la resistance a l'usure et a la fatigue en durcissant les zones critiques superficielles par des apports thermiques courts et localises. Parmi les procedes qui se distinguent par leur capacite en terme de puissance surfacique, le traitement thermique de surface au laser offre des cycles thermiques rapides, localises et precis tout en limitant les risques de deformations indesirables. Les proprietes mecaniques de la zone durcie obtenue par ce procede dependent des proprietes physicochimiques du materiau a traiter et de plusieurs parametres du procede. Pour etre en mesure d'exploiter adequatement les ressources qu'offre ce procede, il est necessaire de developper des strategies permettant de controler et regler les parametres de maniere a produire avec precision les caracteristiques desirees pour la surface durcie sans recourir au classique long et couteux processus essai-erreur. L'objectif du projet consiste donc a developper des modeles pour predire le profil de durete dans le cas de traitement thermique de pieces en acier AISI 4340. Pour comprendre le comportement du procede et evaluer les effets des differents parametres sur la qualite du traitement, une etude de sensibilite a ete menee en se basant sur une planification experimentale structuree combinee a des techniques d'analyse statistiques eprouvees. Les resultats de cette etude ont permis l'identification des variables les plus pertinentes a exploiter pour la modelisation. Suite a cette analyse et dans le but d'elaborer un premier modele, deux techniques de modelisation ont ete considerees, soient la regression multiple et les reseaux de neurones. Les deux techniques ont conduit a des modeles de qualite acceptable avec une precision d'environ 90%. Pour ameliorer les performances des modeles a base de reseaux de neurones, deux

  15. Dynamic approach to predict pH profiles of biologically relevant buffers

    Directory of Open Access Journals (Sweden)

    K. Ganesh

    2017-03-01

    Full Text Available Recently, dynamic approach has been applied to determine the steady state concentrations of multiple ionic species present in complex buffers at equilibrium. Here, we have used the dynamic approach to explicitly model the pH profiles of biologically relevant phosphate buffer and universal buffer (a mixture of three tri-protic acids such as citric acid, boric acid and phosphoric acid. The results from dynamic approach are identical to that of the conventional algebraic approach, but with an added advantage that the dynamic approach, allow for the modelling of complex buffer systems relatively easy compared to that of algebraic method.

  16. Cocaine profiling: Implementation of a predictive model by ATR-FTIR coupled with chemometrics in forensic chemistry.

    Science.gov (United States)

    Materazzi, Stefano; Gregori, Adolfo; Ripani, Luigi; Apriceno, Azzurra; Risoluti, Roberta

    2017-05-01

    In this study, a strategy based on Infrared Spectroscopy with Fourier Transformed and Attenuated Total Reflectance associated with chemometrics (ATR-FTIR) is proposed to identify the chemical "fingerprint" of cocaine samples. To this end, standard mixtures of cocaine and cuttings at differents ratio were investigated in order to develop a multivariate classification model to simultaneously predict the composition of the samples and to obtain a profile of adulteration of cocaine seizures. In addition, the application of a Partial Least Squares (PLS) and Principal Component Regression (PCR) calibration approaches were found to be a useful tool to predict the content of cocaine, caffeine, procaine, lidocaine and phenacetin in drug seizures. The achieved results on real confiscated samples, in cooperation with the Italian Scientific Investigation Department (Carabinieri-RIS) of Rome, allow to consider ATR-FTIR followed to chemometrics as a promising forensic tool in such situations involving profile comparisons and supporting forensic investigations. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

    Science.gov (United States)

    Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

    2014-01-01

    Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

  18. Automatic selection of reference taxa for protein–protein interaction prediction with phylogenetic profiling

    DEFF Research Database (Denmark)

    Simonsen, Martin; Maetschke, Stefan R.; Ragan, Mark A

    2012-01-01

    : We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...

  19. Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

    Science.gov (United States)

    S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

    2012-01-01

    Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

  20. Profiles of Verbal Working Memory Growth Predict Speech and Language Development in Children with Cochlear Implants

    Science.gov (United States)

    Kronenberger, William G.; Pisoni, David B.; Harris, Michael S.; Hoen, Helena M.; Xu, Huiping; Miyamoto, Richard T.

    2013-01-01

    Purpose: Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of…

  1. Computational analysis of image-based drug profiling predicts synergistic drug combinations: applications in triple-negative breast cancer.

    Science.gov (United States)

    Brandl, Miriam B; Pasquier, Eddy; Li, Fuhai; Beck, Dominik; Zhang, Sufang; Zhao, Hong; Kavallaris, Maria; Wong, Stephen T C

    2014-12-01

    An imaged-based profiling and analysis system was developed to predict clinically effective synergistic drug combinations that could accelerate the identification of effective multi-drug therapies for the treatment of triple-negative breast cancer and other challenging malignancies. The identification of effective drug combinations for the treatment of triple-negative breast cancer (TNBC) was achieved by integrating high-content screening, computational analysis, and experimental biology. The approach was based on altered cellular phenotypes induced by 55 FDA-approved drugs and biologically active compounds, acquired using fluorescence microscopy and retained in multivariate compound profiles. Dissimilarities between compound profiles guided the identification of 5 combinations, which were assessed for qualitative interaction on TNBC cell growth. The combination of the microtubule-targeting drug vinblastine with KSP/Eg5 motor protein inhibitors monastrol or ispinesib showed potent synergism in 3 independent TNBC cell lines, which was not substantiated in normal fibroblasts. The synergistic interaction was mediated by an increase in mitotic arrest with cells demonstrating typical ispinesib-induced monopolar mitotic spindles, which translated into enhanced apoptosis induction. The antitumour activity of the combination vinblastine/ispinesib was confirmed in an orthotopic mouse model of TNBC. Compared to single drug treatment, combination treatment significantly reduced tumour growth without causing increased toxicity. Image-based profiling and analysis led to the rapid discovery of a drug combination effective against TNBC in vitro and in vivo, and has the potential to lead to the development of new therapeutic options in other hard-to-treat cancers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  2. Predicting Ga and Cu Profiles in Co-Evaporated Cu(In,Ga)Se2 Using Modified Diffusion Equations and a Spreadsheet

    Energy Technology Data Exchange (ETDEWEB)

    Repins, Ingrid L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Harvey, Steven P [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bowers, Karen A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Glynn, Stephen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mansfield, Lorelle M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-05-15

    Cu(In,Ga)Se2 (CIGS) photovoltaic absorbers frequently develop Ga gradients during growth. These gradients vary as a function of growth recipe, and are important to device performance. Prediction of Ga profiles using classic diffusion equations is not possible because In and Ga atoms occupy the same lattice sites and thus diffuse interdependently, and there is not yet a detailed experimental knowledge of the chemical potential as a function of composition that describes this interaction. We show how diffusion equations can be modified to account for site sharing between In and Ga atoms. The analysis has been implemented in an Excel spreadsheet, and outputs predicted Cu, In, and Ga profiles for entered deposition recipes. A single set of diffusion coefficients and activation energies are chosen, such that simulated elemental profiles track with published data and those from this study. Extent and limits of agreement between elemental profiles predicted from the growth recipes and the spreadsheet tool are demonstrated.

  3. A protein structural classes prediction method based on PSI-BLAST profile.

    Science.gov (United States)

    Ding, Shuyan; Yan, Shoujiang; Qi, Shuhua; Li, Yan; Yao, Yuhua

    2014-07-21

    Knowledge of protein structural classes plays an important role in understanding protein folding patterns. Prediction of protein structural class based solely on sequence data remains to be a challenging problem. In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM). A total of 3600 features are extracted, then, 278 features are selected by a filter feature selection method based on 1189 dataset. To verify the performance of our method (named by LCC-PSSM), jackknife tests are performed on three widely used low similarity benchmark datasets. Comparison of our results with the existing methods shows that our method provides the favorable performance for protein structural class prediction. Stand-alone version of the proposed method (LCC-PSSM) is written in MATLAB language and it can be downloaded from http://bioinfo.zstu.edu.cn/LCC-PSSM/. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile

    Directory of Open Access Journals (Sweden)

    Shuyan Ding

    2016-01-01

    Full Text Available Prediction of secreted protein types based solely on sequence data remains to be a challenging problem. In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM. A total of 6800 features are extracted at 17 different gaps; then, 309 features are selected by a filter feature selection method based on the training set. To verify the performance of our method, jackknife and independent dataset tests are performed on the test set and the reported overall accuracies are 93.60% and 100%, respectively. Comparison of our results with the existing method shows that our method provides the favorable performance for secreted protein type prediction.

  5. Profile of the Pleximmune blood test for transplant rejection risk prediction

    OpenAIRE

    Sindhi, Rakesh; Ashokkumar, Chethan; Higgs, Brandon W; Levy, Samantha; Soltys, Kyle; Bond, Geoffrey; Mazariegos, George; Ranganathan, Sarangarajan; Zeevi, Adriana

    2016-01-01

    The Pleximmune? test (Plexision Inc., Pittsburgh, PA, USA) is the first cell-based test approved by the US FDA, which predicts acute cellular rejection in children with liver- or intestine transplantation. The test addresses an unmet need to improve management of immunosuppression, which incurs greater risks of opportunistic infections and Epstein?Barr virus-induced malignancy during childhood. High-dose immunosuppression and recurrent rejection after intestine transplantation also result in ...

  6. Profile of the Pleximmune blood test for transplant rejection risk prediction

    Science.gov (United States)

    Sindhi, Rakesh; Ashokkumar, Chethan; Higgs, Brandon W; Levy, Samantha; Soltys, Kyle; Bond, Geoffrey; Mazariegos, George; Ranganathan, Sarangarajan; Zeevi, Adriana

    2016-01-01

    Summary The Pleximmune™ test (Plexision Inc., Pittsburgh, PA, USA) is the first cell-based test approved by the US FDA, which predicts acute cellular rejection in children with liver- or intestine transplantation. The test addresses an unmet need to improve management of immunosuppression, which incurs greater risks of opportunistic infections and Epstein–Barr virus-induced malignancy during childhood. High-dose immunosuppression and recurrent rejection after intestine transplantation also result in a 5-year graft loss rate of up to 50%. Such outcomes seem increasingly unacceptable because children can experience rejection-free survival with reduced immunosuppression. Pleximmune test sensitivity and specificity for predicting acute cellular rejection is 84% and 81% respectively in training set–validation set testing of 214 children. Among existing gold standards, the biopsy detects but cannot predict rejection. Anti-donor antibodies, which presage antibody-mediated injury, reflect late-stage allosensitization as a downstream effect of engagement between recipient and donor cells. Therefore, durable graft and patient outcomes also require an accurate management of cellular immune responses in clinical practice. PMID:26760313

  7. A novel method for predicting post-translational modifications on serine and threonine sites by using site-modification network profiles.

    Science.gov (United States)

    Wang, Minghui; Jiang, Yujie; Xu, Xiaoyi

    2015-11-01

    Post-translational modifications (PTMs) regulate many aspects of biological behaviours including protein-protein interactions and cellular processes. Identification of PTM sites is helpful for understanding the PTM regulatory mechanisms. The PTMs on serine and threonine sites include phosphorylation, O-linked glycosylation and acetylation. Although a lot of computational approaches have been developed for PTM site prediction, currently most of them generate the predictive models by employing only local sequence information and few of them consider the relationship between different PTMs. In this paper, by adopting the site-modification network (SMNet) profiles that efficiently incorporate in situ PTM information, we develop a novel method to predict PTM sites on serine and threonine. PTM data are collected from various PTM databases and the SMNet is built to reflect the relationship between multiple PTMs, from which SMNet profiles are extracted to train predictive models based on SVM. Performance analysis of the SVM models shows that the SMNet profiles play an important role in accurately predicting PTM sites on serine and threonine. Furthermore, the proposed method is compared with existing PTM prediction approaches. The results from 10-fold cross-validation demonstrate that the proposed method with SMNet profiles performs remarkably better than existing methods, suggesting the power of SMNet profiles in identifying PTM sites.

  8. Effect of dietary vitamin E on the oxidative stability, flavor, color, and volatile profiles of refrigerated and frozen turkey breast meat.

    Science.gov (United States)

    Sheldon, B W; Curtis, P A; Dawson, P L; Ferket, P R

    1997-04-01

    In this study, the effect of varying dietary vitamin E levels on the oxidative stability, flavor, color, and volatile profiles of refrigerated and frozen turkey breast meat was examined. Nicholas turkey toms were reared on diets containing vitamin E levels as dl-alpha-tocopheryl acetate equivalent to the NRC recommendations (12 and 10 IU/kg from 0 to 8 and 9 to 18 wk, respectively) and 5x, 10x, and 25x the NRC diet. Two other diets were evaluated and included feeding the NRC diet until 15 and 16 wk followed by a diet containing 20x the NRC vitamin E level. All turkeys were processed in a commercial turkey processing plant and breast meat scored for color. Breast meat was excised from four carcasses per treatment and evaluated after refrigeration (1 and 7 d) or frozen storage (30, 90, 150 d) for oxidative stability and sensory quality by TBA analysis, descriptive flavor profiling, and headspace gas chromatography. The TBA values were inversely related to the dietary vitamin E levels. Refrigerated samples had TBA values 78 to 88% lower for the 10x and 25x vitamin E treatments, respectively, than for the NRC control treatment. No differences in TBA values (refrigerated samples) were detected for the 10x, 25x, and 20x (3 wk feeding duration) or across all treatments for samples frozen for 5 mo. The 10x and 25x NRC diets produced the most typical and acceptable turkey meat flavors with the fewest oxidized off-flavor notes for both fresh and frozen samples as opposed to the more oxidized flavor notes detected in the control samples. Mean color scores increased, indicative of less pale meat, as the level and duration of feeding dietary vitamin E increased. These findings showed that varying dietary vitamin E levels significantly influenced the oxidative stability and functionality of turkey breast meat.

  9. Stabilization of lysosomal membrane and cell membrane glycoprotein profile by Semecarpus anacardium linn. nut milk extract in experimental hepatocellular carcinoma.

    Science.gov (United States)

    Premalatha, B; Sachdanandam, P

    2000-08-01

    Semecarpus anacardium Linn. nut milk extract administered orally at a dose of 200 mg/kg/day for 14 days exerted an in vivo stabilizing effect on lysosomal membrane and glycoprotein content in rat hepatocellular carcinoma. This was demonstrated in normal rats and in animals whose biomembranes were rendered fragile by induction of hepatocellular carcinoma with aflatoxin B(1) and subsequent treatment with Semecarpus anacardium nut extract. In this condition, the discharge of lysosomal enzymes increased significantly with a subsequent increase in glycoprotein components. The nut extract administration reversed these adverse changes to near normal in treated animals. The possible reason for this reversal is discussed. Such stabilization of biomembranes by Semecarpus anacardium nut extract may have a beneficial effect in the treatment of hepatocellular carcinoma and other cancers involving abnormal fragility of lysosomes and glycoprotein content providing the extract demonstrates safety in a full toxicity study. Copyright 2000 John Wiley & Sons, Ltd.

  10. Influence of stability on the flux-profile relationships for wind speed, Φm, and temperature, Φh, for the stable atmospheric boundary layer

    Directory of Open Access Journals (Sweden)

    C. Yagüe

    2006-01-01

    Full Text Available Data from SABLES98 experimental campaign have been used in order to study the influence of stability (from weak to strong stratification on the flux-profile relationships for momentum, Φm, and heat, Φh. Measurements from 14 thermocouples and 3 sonic anemometers at three levels (5.8, 13.5 and 32 m for the period from 10 to 28 September 1998 were analysed using the framework of the local-scaling approach (Nieuwstadt, 1984a; 1984b, which can be interpreted as an extension of the Monin-Obukhov similarity theory (Obukhov, 1946. The results show increasing values of Φm and Φh with increasing stability parameter ζ=z/Λ, up to a value of ζ≈1–2, above which the values remain constant. As a consequence of this levelling off in Φm and Φh for strong stability, the turbulent mixing is underestimated when linear similarity functions (Businger et al., 1971 are used to calculate surface fluxes of momentum and heat. On the other hand when Φm and Φh are related to the gradient Richardson number, Ri, a different behaviour is found, which could indicate that the transfer of momentum is greater than that of heat for high Ri. The range of validity of these linear functions is discussed in terms of the physical aspects of turbulent intermittent mixing.

  11. Impact of feeding chromium supplemented flaxseed based diet on fatty acid profile, oxidative stability and other functional properties of broiler chicken meat.

    Science.gov (United States)

    Mir, Nasir Akbar; Tyagi, Praveen K; Biswas, A K; Tyagi, Pramod K; Mandal, A B; Sheikh, Sajad A; Deo, Chandra; Sharma, Divya; Verma, A K

    2017-11-01

    A total of 240 broiler chicken of same hatch with uniform weight were used in a biological experiment with completely randomized design to investigate the effects of incorporating organic chromium (Cr) in flaxseed meal based diet on the fatty acid profile, oxidative stability and functional properties of broiler chicken meat. Five diets were formulated as per the recommendations of BIS (Nutrient requirements for poultry 13: 9863, Bureau of Indian Standards, New Delhi, 1992) in which flaxseed meal was used to replace 10% of soyabean in basal diet and four levels of Cr (0.0, 0.5, 1.0 and 1.5 mg/kg diet) as Cr-picolinate were used. The results revealed that flaxseed feeding significantly increased the percentage of unsaturated fatty acids, including MUFA, PUFA, ω-3, ω-6 fatty acids and ω-3:ω-6 and PUFA:SFA ratios, whereas, significant decline was seen in saturated fatty acids and no effect of Cr was observed on the fatty acid profile of broiler chicken. Flaxseed feeding significantly reduced the cholesterol and fat percentage of meat, whereas, significant progressive reduction was observed with increasing Cr levels. The combination of 10% flaxseed with 1.0 mg Cr/kg diet increased the final pH of broiler meat. The addition of flaxseed significantly reduced water holding capacity, extract release volume and antioxidant potential of broiler meat, whereas, increasing Cr supplementation progressively increased them. Flaxseed feeding significantly increased the drip loss and lipid peroxidation of broiler meat, whereas, Cr supplementation decreased them. It was concluded that inclusion of 10% flaxseed and 1.5 mg Cr/kg diet results in desirable fatty acid profile, oxidative stability and functional properties of broiler chicken meat.

  12. Gradient Correlation Method for the Stabilization of Inversion Results of Aerosol Microphysical Properties Retrieved from Profiles of Optical Data

    Directory of Open Access Journals (Sweden)

    Kolgotin Alexei

    2016-01-01

    Full Text Available Correlation relationships between aerosol microphysical parameters and optical data are investigated. The results show that surface-area concentrations and extinction coefficients are linearly correlated with a correlation coefficient above 0.99 for arbitrary particle size distribution. The correlation relationships that we obtained can be used as constraints in our inversion of optical lidar data. Simulation studies demonstrate a significant stabilization of aerosol microphysical data products if we apply the gradient correlation method in our traditional regularization technique.

  13. Early Identification of Children at Risk for Academic Difficulties Using Standardized Assessment: Stability and Predictive Validity of Preschool Math and Language Scores

    Science.gov (United States)

    Frans, Niek; Post, Wendy J.; Huisman, Mark; Oenema-Mostert, Ineke C. E.; Keegstra, Anne L.; Minnaert, Alexander E. M. G.

    2017-01-01

    Despite the claim by several researchers that variability in performance may complicate the identification of "at-risk" children, variability in the academic performance of young children remains an undervalued area of research. The goal of this study is to examine the predictive validity for future scores and the score stability of two…

  14. Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile.

    Directory of Open Access Journals (Sweden)

    Twan van Laarhoven

    Full Text Available In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction. Drug-target interaction data are available for many classes of pharmaceutically useful target proteins including enzymes, ion channels, GPCRs and nuclear receptors. However, current drug-target interaction databases contain a small number of drug-target pairs which are experimentally validated interactions. In particular, for some drug compounds (or targets there is no available interaction. This motivates the need for developing methods that predict interacting pairs with high accuracy also for these 'new' drug compounds (or targets. We show that a simple weighted nearest neighbor procedure is highly effective for this task. We integrate this procedure into a recent machine learning method for drug-target interaction we developed in previous work. Results of experiments indicate that the resulting method predicts true interactions with high accuracy also for new drug compounds and achieves results comparable or better than those of recent state-of-the-art algorithms. Software is publicly available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2013/.

  15. Changes in cytokine profile may predict therapeutic efficacy of infliximab in patients with ulcerative colitis.

    Science.gov (United States)

    Sato, Shoko; Chiba, Toshimi; Nakamura, Shotaro; Matsumoto, Takayuki

    2015-10-01

    Infliximab is an established therapy for ulcerative colitis (UC). The aim of this study was to examine various serum cytokine levels and to identify possible markers predictive of therapeutic efficacy of infliximab for UC patients. Twenty-one patients with moderately active UC were given intravenous infliximab (5 mg/kg) at 0, 2, and 6 weeks as induction therapy. The serum levels of 17 cytokines were determined using a Bio-Plex suspension array system before and 8 weeks after induction therapy. Partial Mayo score (PMS) and serum C-reactive protein levels were used for the determination of clinical activities at 0 and 8 weeks after the treatment. The overall therapeutic effect was determined at 26 weeks according to the PMS. The median value of the PMS decreased significantly 8 weeks after the treatment (from 6 to 1.5, P infliximab, while IL-6 at 8 weeks after induction therapy may be predictive of subsequent response to infliximab. © 2015 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

  16. Prediction of the maximum temperature for life based on the stability of metabolites to decomposition in water.

    Science.gov (United States)

    Bains, William; Xiao, Yao; Yu, Changyong

    2015-03-26

    The components of life must survive in a cell long enough to perform their function in that cell. Because the rate of attack by water increases with temperature, we can, in principle, predict a maximum temperature above which an active terrestrial metabolism cannot function by analysis of the decomposition rates of the components of life, and comparison of those rates with the metabolites' minimum metabolic half-lives. The present study is a first step in this direction, providing an analytical framework and method, and analyzing the stability of 63 small molecule metabolites based on literature data. Assuming that attack by water follows a first order rate equation, we extracted decomposition rate constants from literature data and estimated their statistical reliability. The resulting rate equations were then used to give a measure of confidence in the half-life of the metabolite concerned at different temperatures. There is little reliable data on metabolite decomposition or hydrolysis rates in the literature, the data is mostly confined to a small number of classes of chemicals, and the data available are sometimes mutually contradictory because of varying reaction conditions. However, a preliminary analysis suggests that terrestrial biochemistry is limited to environments below ~150-180 °C. We comment briefly on why pressure is likely to have a small effect on this.

  17. Prediction of the Maximum Temperature for Life Based on the Stability of Metabolites to Decomposition in Water

    Directory of Open Access Journals (Sweden)

    William Bains

    2015-03-01

    Full Text Available The components of life must survive in a cell long enough to perform their function in that cell. Because the rate of attack by water increases with temperature, we can, in principle, predict a maximum temperature above which an active terrestrial metabolism cannot function by analysis of the decomposition rates of the components of life, and comparison of those rates with the metabolites’ minimum metabolic half-lives. The present study is a first step in this direction, providing an analytical framework and method, and analyzing the stability of 63 small molecule metabolites based on literature data. Assuming that attack by water follows a first order rate equation, we extracted decomposition rate constants from literature data and estimated their statistical reliability. The resulting rate equations were then used to give a measure of confidence in the half-life of the metabolite concerned at different temperatures. There is little reliable data on metabolite decomposition or hydrolysis rates in the literature, the data is mostly confined to a small number of classes of chemicals, and the data available are sometimes mutually contradictory because of varying reaction conditions. However, a preliminary analysis suggests that terrestrial biochemistry is limited to environments below ~150–180 °C. We comment briefly on why pressure is likely to have a small effect on this.

  18. How Childhood Maltreatment Profiles of Male Victims Predict Adult Perpetration and Psychosocial Functioning

    Science.gov (United States)

    Davis, Kelly Cue; Masters, N. Tatiana; Casey, Erin; Kajumulo, Kelly F.; Norris, Jeanette; George, William H.

    2016-01-01

    This study used latent class analysis to empirically identify subgroups of men based on their exposure to childhood maltreatment (i.e., emotional neglect and abuse, physical neglect and abuse, and sexual abuse). It then examined subgroups’ differential perpetration of adult intimate partner violence (both psychological and physical), violence against peers, and sexual assault. Finally, we compared socio-demographic variables and psychosocial functioning across profiles to characterize the adult experiences of men in different maltreatment groups. The community sample consisted of 626 heterosexually active 21–30 year old men. We identified four subgroups: Low Maltreatment (80% of the sample), Emotional and Physical Maltreatment (12%), Emotional and Sexual Maltreatment (4%), and Poly-victimized (4%). The Low Maltreatment group had significantly lower IPV perpetration rates than the Emotional and Physical Maltreatment group, but groups did not significantly differ on peer violence or sexual assault perpetration rates. Overall, Poly-victimized men were significantly worse off than the Low Maltreatment group regarding income, education level, and incarceration history. Their rates of recent anxiety and depression symptoms were also higher than those of Low Maltreatment men. Findings support the use of person-oriented techniques for deriving patterns of childhood maltreatment and how these patterns relate to psychological, behavioral, and social factors in adulthood. PMID:26590221

  19. [Social profiles, diet, and prediction of eating disorders in urban andalusian adolescents].

    Science.gov (United States)

    Gil García, Eugenia; Ortiz Gómez, Teresa; Fernández Soto, María Luisa

    2007-01-01

    To know the social profile of Andalusian urban adolescents and analyse the similarities and differences they have with those at risk of presenting with eating disorders. Cross-sectional community study. Stratified cluster sampling. Public and private education institutions in Andalusian cities with more than 100 000 inhabitants (Sevilla, Malaga, Granada, Cordoba, Cadiz, Huelva, Almeria, Jaen, Algeciras, and Jerez). Pupils from 12 to 16 years, attending an academic course in the year 2002-2003 (N=1667). To compare the results of the sample with adolescents who are at risk of presenting with eating disorders (those who scored more than 20 in the 26-item Eating Attitudes Test [EAT-26]) we used the chi2 test for the nominal variables and the Spearman rho for the interval variables, with a significance level of P=.05. There were no differences between either group as regards family structure, friend relationships, academic performance, and sporting activities. The differences centred on disciplinary practices, the number of friends diagnosed with an eating behavioural disorder, the objectives for practicing sports, and the type of diet that they followed. The subjects who scored highest on the EAT-26 were those who had a higher body mass index and a lower social status. It appears that diet changes are a response to certain social conditions. It would be speculative to include subjects who obtain high EAT-26 scores in the population at risk of anorexia.

  20. Predicting Delirium Duration in Elderly Hip-Surgery Patients: Does Early Symptom Profile Matter?

    Directory of Open Access Journals (Sweden)

    Chantal J. Slor

    2013-01-01

    Full Text Available Background. Features that may allow early identification of patients at risk of prolonged delirium, and therefore of poorer outcomes, are not well understood. The aim of this study was to determine if preoperative delirium risk factors and delirium symptoms (at onset and clinical symptomatology during the course of delirium are associated with delirium duration. Methods. This study was conducted in prospectively identified cases of incident delirium. We compared patients experiencing delirium of short duration (1 or 2 days with patients who had more prolonged delirium (≥3 days with regard to DRS-R-98 (Delirium Rating Scale Revised-98 symptoms on the first delirious day. Delirium symptom profile was evaluated daily during the delirium course. Results. In a homogenous population of 51 elderly hip-surgery patients, we found that the severity of individual delirium symptoms on the first day of delirium was not associated with duration of delirium. Preexisting cognitive decline was associated with prolonged delirium. Longitudinal analysis using the generalised estimating equations method (GEE identified that more severe impairment of long-term memory across the whole delirium episode was associated with longer duration of delirium. Conclusion. Preexisting cognitive decline rather than severity of individual delirium symptoms at onset is strongly associated with delirium duration.

  1. Prediction of neonates' macrosomia with maternal lipid profile of healthy mothers.

    Science.gov (United States)

    Mossayebi, Elaheh; Arab, Zohreh; Rahmaniyan, Mojgan; Almassinokiani, Fariba; Kabir, Ali

    2014-02-01

    The aim of this study is to identify the association between the lipid profile of healthy nondiabetic, nonobese pregnant women in the first weeks of the third trimester of pregnancy and macrosomia or large-for-gestational-age (LGA) neonates with normal pregnancies. In this cohort study, 200 pregnant healthy women without gestational diabetes mellitus (GDM), obesity, or hypertension and carrying a single fetus in a prenatal clinic of a referral hospital were included based on a convenience sampling. Then, we took a blood sample to assess fasting blood sugar (FBS), triglyceride (TG), total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL). GDM was assessed after administering 50 g of oral glucose. All cases were followed until the end of pregnancy. The main outcome measurement was neonatal birth weight. Only 154 mothers met eligibility criteria. There were eight cases (5.2%) with macrosomia (birth weight ≥ 4000 g) and 35 cases (22.7%) with LGA. Linear regression showed that mothers' TG and neonates' gender were independent predictors of the birth weight of the children (R-square = 0.52, p macrosomia (Nagelkerke R-square = 0.53, p macrosomia (birth weight > 4500 g), but also for LGA. Copyright © 2013. Published by Elsevier B.V.

  2. Molecular Profiling Predicts the Existence of Two Functionally Distinct Classes of Ovarian Cancer Stroma

    Directory of Open Access Journals (Sweden)

    Loukia N. Lili

    2013-01-01

    Full Text Available Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0 gene expression platform. Laser capture microdissection (LCM was employed to isolate cancer cells from the tumors of ovarian cancer patients (Cepi and matched sets of surrounding cancer stroma (CS. For controls, ovarian surface epithelial cells (OSE were isolated from the normal (noncancerous ovaries and normal stroma (NS. Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples. Expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples indicate the existence of two subgroups of cancer stroma (CS with different propensities to support tumor growth. Our results indicate that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.

  3. Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.

    Science.gov (United States)

    Lili, Loukia N; Matyunina, Lilya V; Walker, L DeEtte; Benigno, Benedict B; McDonald, John F

    2013-01-01

    Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of ovarian cancer patients (Cepi) and matched sets of surrounding cancer stroma (CS). For controls, ovarian surface epithelial cells (OSE) were isolated from the normal (noncancerous) ovaries and normal stroma (NS). Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples. Expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples indicate the existence of two subgroups of cancer stroma (CS) with different propensities to support tumor growth. Our results indicate that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.

  4. Predictions of methane emission levels and categories based on milk fatty acid profiles from dairy cows.

    Science.gov (United States)

    Castro-Montoya, J M; Peiren, N; Veneman, J; De Baets, B; De Campeneere, S; Fievez, V

    2017-07-01

    Milk fatty acid (MFA) have already been used to model methane (CH4) emissions from dairy cows. However, the data sets used to develop these models covered limited variation in dietary conditions, reducing the robustness of the predictions. In this study, a data set containing 140 observations from nine experiments (41 Holstein cows) was used to develop models predicting CH4 expressed as g/day, g/kg dry matter intake (DMI) and g/kg milk. The data set was divided into a training (n=112) and a test data set (n=28) for model development and validation, respectively. A generalized linear mixed model was fitted to the data using the marginal R 2 (m) and the Akaike information criterion to evaluate the models. The coefficient of determination of validation (R 2 (v)) for different models developed ranged between 0.18 and 0.41. Form the intake-related parameters, only inclusion of total DMI improved the prediction (R 2 (v)=0.58). In addition, in an attempt to further explore the relationships between MFA and CH4 emissions, the data set was split into three categories according to CH4 emissions: LOW (lowest 25% CH4 emissions); HIGH (highest 25% CH4 emissions); and MEDIUM (50% remaining observations). An ANOVA revealed that concentrations of several MFA differed for observations in HIGH compared with observations in LOW. Furthermore, the Gini coefficient was used to describe the MFA distribution for groups of MFA in each CH4 emission category. The relative distribution of the MFA, particularly of the odd- and branched-chain fatty acids and mono-unsaturated fatty acids of observations in category HIGH differed from those in the other categories. Finally, in an attempt to validate the potential of MFA to identify cases of high or low emissions, the observations were re-classified into HIGH, MEDIUM and LOW according to the proportion of each individual MFA. The proportion of observations correctly classified were recorded. This was done for each individual MFA and for the

  5. Stabilization of dendritic spine clusters and hyperactive Ras-MAPK signaling predict enhanced motor learning in an autistic savant mouse model

    Directory of Open Access Journals (Sweden)

    Ryan Thomas Ash

    2014-03-01

    Full Text Available That both prominent behavioral inflexibility and exceptional learning abilities are seen occasionally in autistic patients is a mystery. We hypothesize that these altered patterns of learning and memory can arise from a pathological imbalance between the stability and plasticity of internal neural representations. We evaluated this hypothesis in the mouse model of MECP2 duplication syndrome, which demonstrates enhanced motor learning, stereotyped behaviors, and social avoidance. Learning-associated structural plasticity was measured in the motor cortex of MECP2 duplication mice by 2-photon imaging (Fig. 1A. An increased stabilization rate of learning-associated dendritic spines was observed in mutants, and this correlated with rotarod performance. Analysis of the spatial distribution of stabilized spines revealed that the mutant’s increased spine stabilization was due to a specific increase in the stability of spines jointly formed in ~9-micron clusters. Clustered spine stabilization but not isolated spine stabilization predicted enhanced motor performance in MECP2 duplication mice (Fig. 1B. Biochemical assays of Ras-MAPK and mTOR pathway activation demonstrated profound hyperphosphorylation of MAPK in the motor cortex of MECP2 duplication mice with motor training (Fig. 1C. Taken together these data suggest that a pathological bias towards hyperstability of learning-associated dendritic spine clusters driven by hyperactive Ras-MAPK signaling could contribute to neurobehavioral phenotypes in this form of syndromic autism.

  6. Computational fluid dynamics (CFD prediction of mass fraction profiles of gas oil and gasoline in fluid catalytic cracking (FCC riser

    Directory of Open Access Journals (Sweden)

    Muhammad Ahsan

    2012-12-01

    Full Text Available Fluid catalytic cracking (FCC is an important process for the conversion of gas oil to gasoline. The paper is an attempt to model the phenomenon theoretically; using commercial computational fluid dynamics (CFD software and 3-lump kinetic model. Geometry, boundary conditions and dimensions of industrial riser for catalytic cracking unit is conferred for 2D simulation using commercial CFD code. Continuity, momentum, energy and species transport equations, applicable to two phase solid and gas flow, are used to simulate the physical phenomenon efficiently. This paper uses the granular Eulerian multiphase model with k–ε turbulence and species transport. Time accurate transient problem is solved with the prediction of mass fraction profiles of gas oil, gasoline, light gas and coke. The output curves demonstrate the mass fraction and distribution of temperature in both phases. At the end comparison of the computational results with other computational and experimental data available in literature is also given.

  7. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors.

    Science.gov (United States)

    de Jong, Monique C; Pramana, Jimmy; Knegjens, Joost L; Balm, Alfons J M; van den Brekel, Michiel W M; Hauptmann, Michael; Begg, Adrian C; Rasch, Coen R N

    2010-06-01

    The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. Gene expression data were available for a series of 92 advanced stage head and neck cancer patients treated with primary chemoradiotherapy. The effect of the Chung high-risk and Slebos HPV expression profiles on local control was analyzed in a model with age at diagnosis, gender, tumor site, tumor volume, T-stage and N-stage and HPV profile status. Among 75 patients included in the study, the only factors significantly predicting local control were tumor site (oral cavity vs. Pharynx, hazard ratio 4.2 [95% CI 1.4-12.5]), Chung gene expression status (high vs. Low risk profile, hazard ratio 4.4 [95% CI 1.5-13.3]) and HPV profile (negative vs. Positive profile, hazard ratio 6.2 [95% CI 1.7-22.5]). Chung high-risk expression profile and a negative HPV expression profile were significantly associated with increased risk of local recurrence after chemoradiotherapy in advanced pharynx and oral cavity tumors, independent of clinical factors. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

  8. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

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    Minseung Kim

    2015-03-01

    Full Text Available A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5% to 98.3% (±2.3% for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain achieved 10.6% (±1.0% higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  9. Lyα Profile, Dust, and Prediction of Lyα Escape Fraction in Green Pea Galaxies

    Science.gov (United States)

    Yang, Huan; Malhotra, Sangeeta; Gronke, Max; Rhoads, James E.; Leitherer, Claus; Wofford, Aida; Jiang, Tianxing; Dijkstra, Mark; Tilvi, V.; Wang, Junxian

    2017-08-01

    We studied Lyman-α (Lyα) escape in a statistical sample of 43 Green Peas with HST/COS Lyα spectra. Green Peas are nearby star-forming galaxies with strong [O iii]λ5007 emission lines. Our sample is four times larger than the previous sample and covers a much more complete range of Green Pea properties. We found that about two-thirds of Green Peas are strong Lyα line emitters with rest-frame Lyα equivalent width > 20 \\mathringA . The Lyα profiles of Green Peas are diverse. The Lyα escape fraction, defined as the ratio of observed Lyα flux to intrinsic Lyα flux, shows anti-correlations with a few Lyα kinematic features—both the blue peak and red peak velocities, the peak separations, and the FWHM of the red portion of the Lyα profile. Using properties measured from Sloan Digital Sky Survey optical spectra, we found many correlations—the Lyα escape fraction generally increases at lower dust reddening, lower metallicity, lower stellar mass, and higher [O iii]/[O ii] ratio. We fit their Lyα profiles with the H i shell radiative transfer model and found that the Lyα escape fraction is anti-correlated with the best-fit N H i . Finally, we fit an empirical linear relation to predict {f}{esc}{Lyα } from the dust extinction and Lyα red peak velocity. The standard deviation of this relation is about 0.3 dex. This relation can be used to isolate the effect of intergalactic medium (IGM) scatterings from Lyα escape and to probe the IGM optical depth along the line of sight of each z> 7 Lyα emission-line galaxy in the James Webb Space Telescope era.

  10. Developing a Comparative Docking Protocol for the Prediction of Peptide Selectivity Profiles: Investigation of Potassium Channel Toxins

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    Serdar Kuyucak

    2012-02-01

    Full Text Available During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to “predict” the various selectivity profiles of several major αKTX scorpion toxin families versus Kv1.1, Kv1.2 and Kv1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and Kv1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.

  11. Biomechanical Comparison of Locking Compression Plate versus Positive Profile Pins and Polymethylmethacrylate for Stabilization of the Canine Lumbar Vertebrae.

    Science.gov (United States)

    Sturges, Beverly K; Kapatkin, Amy S; Garcia, Tanya C; Anwer, Cona; Fukuda, Shimpei; Hitchens, Peta L; Wisner, Tristan; Hayashi, Kei; Stover, Susan M

    2016-04-01

    To compare the stiffness, angular deformation, and mode of failure of lumbar vertebral column constructs stabilized with bilateral pins and polymethylmethacrylate (Pin-PMMA) or with a unilateral (left) locking compression plate (LCP) with monocortical screws. Ex vivo biomechanical, non-randomized. Cadaveric canine thoracolumbar specimens (n=16). Thoracolumbar (T13-L3) vertebral specimens had the L1-L2 vertebral motion unit stabilized with either Pin-PMMA or LCP. Stiffness in flexion, extension, and right and left lateral bending after nondestructive testing were compared between intact (pretreated) specimens and Pin-PMMA, and LCP constructs. The Pin-PMMA and LCP constructs were then tested to failure in flexion and left lateral bending. Both the Pin-PMMA and LCP constructs had reduced range of motion at the stabilized L1-L2 vertebral motion unit compared to intact specimens. The Pin-PMMA constructs had less range of motion for the flexion elastic zone than LCP constructs. The Pin-PMMA constructs were stiffer than intact specimens in flexion, extension, and lateral bending, and stiffer than LCP constructs in flexion and left lateral bending. The Pin-PMMA constructs had less angular deformation at construct yield and lower residual deformation at L1-L2 than LCP constructs after destructive testing to failure in flexion. The Pin-PMMA constructs were stiffer, stronger, and had less deformation at yield than LCP constructs after destructive testing to failure in lateral bending. Most constructs failed distant to the implant and fixation site. Pin-PMMA constructs had greater lumbar vertebral stiffness and reduced ROM than LCP constructs; however, both Pin-PMMA and LCP constructs were stronger than intact specimens. © Copyright 2016 by The American College of Veterinary Surgeons.

  12. [Effect of air humidity on traditional Chinese medicine extract of spray drying process and prediction of its powder stability].

    Science.gov (United States)

    He, Yan; Xie, Yin; Zheng, Long-jin; Liu, Wei; Rao, Xiao-yong; Luo, Xiao-jian

    2015-02-01

    In order to solve the adhesion and the softening problems of traditional Chinese medicine extract during spray drying, a new method of adding dehumidified air into spray drying process was proposed, and the storage stability conditions of extract powder could be predicted. Kouyanqing extract was taken as model drug to investigate on the wet air (RH = 70%) and dry air conditions of spray drying. Under the dry air condition, the influence of the spray drying result with different air compression ratio and the spray-dried powder properties (extract powder recovery rate, adhesion percentage, water content, angle of repose, compression ratio, particle size and distribution) with 100, 110, 120, 130, 140 °C inlet temperature were studied. The hygroscopic investigation and Tg value with different moisture content of ideal powder were determined. The water activity-equilibrium moisture content (aw-EMC) and the equilibrium moisture content-Tg (EMC-Tg) relationships were fitted by GAB equation and Gordon-Taylor model respectively, and the state diagram of kouyanqing powder was obtained to guide the rational storage conditions. The study found that in the condition of dry air, the extract powder water content decreased with the increase of air compression ratio and the spray drying effect with air compression ratio of 100% was the best performance; in the condition of wet air, the extract powder with high water content and low yield, and the value were 4.26% and 16.73 °C, while, in the dry air condition the values were 2.43% and 24.86 °C with the same other instru- ment parameters. From the analysis of kouyanqing powder state diagram, in order to keep the stability, the critical water content of 3.42% and the critical water content of 0.188. As the water decreased Tg value of extract powder is the major problem of causing adhesion and softening during spray drying, it is meaningful to aid dehumidified air during the process.

  13. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI, a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc., the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.

  14. Preliminary assessment of a model to predict mold contamination based on microbial volatile organic compound profiles.

    Science.gov (United States)

    LeBouf, Ryan F; Schuckers, Stephanie A; Rossner, Alan

    2010-08-01

    Identification of mold growth based on microbial volatile organic compounds (MVOCs) may be a viable alternative to current bioaerosol assessment methodologies. A feed-forward back propagation (FFBP) artificial neural network (ANN) was developed to correlate MVOCs with bioaerosol levels in built environments. A cross-validation MATLAB script was developed to train the ANN and produce model results. Entech Bottle-Vacs were used to collect chemical grab samples at 10 locations in northern NY during 17 sampling periods from July 2006 to August 2007. Bioaerosol samples were collected concurrently with chemical samples. An Anderson N6 impactor was used in conjunction with malt extract agar and dichloran glycerol 18 to collect viable mold samples. Non-viable samples were collected with Air-O-Cell cassettes. Chemical samples and bioaerosol samples were used as model inputs and model targets, respectively. Previous researchers have suggested the use of MVOCs as indicators of mold growth without the use of a pattern recognition program limiting their success. The current proposed strategy implements a pattern recognition program making it instrumental for field applications. This paper demonstrates that FFBP ANN may be used in conjunction with chemical sampling in built environments to predict the presence of mold growth. 2010 Elsevier B.V. All rights reserved.

  15. Predicting clinical concussion measures at baseline based on motivation and academic profile.

    Science.gov (United States)

    Trinidad, Katrina J; Schmidt, Julianne D; Register-Mihalik, Johna K; Groff, Diane; Goto, Shiho; Guskiewicz, Kevin M

    2013-11-01

    The purpose of this study was to predict baseline neurocognitive and postural control performance using a measure of motivation, high school grade point average (hsGPA), and Scholastic Aptitude Test (SAT) score. Cross-sectional. Clinical research center. Eighty-eight National Collegiate Athletic Association Division I incoming student-athletes (freshman and transfers). Participants completed baseline clinical concussion measures, including a neurocognitive test battery (CNS Vital Signs), a balance assessment [Sensory Organization Test (SOT)], and motivation testing (Rey Dot Counting). Participants granted permission to access hsGPA and SAT total score. Standard scores for each CNS Vital Signs domain and SOT composite score. Baseline motivation, hsGPA, and SAT explained a small percentage of the variance of complex attention (11%), processing speed (12%), and composite SOT score (20%). Motivation, hsGPA, and total SAT score do not explain a significant amount of the variance in neurocognitive and postural control measures but may still be valuable to consider when interpreting neurocognitive and postural control measures.

  16. Quiescent and Active Tear Protein Profiles to Predict Vernal Keratoconjunctivitis Reactivation.

    Science.gov (United States)

    Micera, Alessandra; Di Zazzo, Antonio; Esposito, Graziana; Sgrulletta, Roberto; Calder, Virginia L; Bonini, Stefano

    2016-01-01

    Vernal keratoconjunctivitis (VKC) is a chronic recurrent bilateral inflammation of the conjunctiva associated with atopy. Several inflammatory and tissue remodeling factors contribute to VKC disease. The aim is to provide a chip-based protein analysis in tears from patients suffering from quiescent or active VKC. This study cohort included 16 consecutive patients with VKC and 10 controls. Participants were subjected to clinical assessment of ocular surface and tear sampling. Total protein quantification, total protein sketch, and protein array (sixty protein candidates) were evaluated. An overall increased Fluorescent Intensity expression was observed in VKC arrays. Particularly, IL1β, IL15, IL21, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, ICAM2, βNGF, NT4, BDNF, βFGF, SCF, MMP1, and MMP2 were increased in quiescent VKC. Of those candidates, only IL1β, IL15, IL21, βNGF, SCF, MMP2, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, and ICAM2 were increased in both active and quiescent VKC. Finally, NT4, βFGF, and MMP1 were highly increased in active VKC. A distinct "protein tear-print" characterizes VKC activity, confirming some previously reported factors and highlighting some new candidates common to quiescent and active states. Those candidates expressed in quiescent VKC might be considered as predictive indicators of VKC reactivation and/or exacerbation out-of-season.

  17. Prediction of Air Flow and Temperature Profiles Inside Convective Solar Dryer

    Directory of Open Access Journals (Sweden)

    Marian Vintilă

    2014-11-01

    Full Text Available Solar tray drying is an effective alternative for post-harvest processing of fruits and vegetables. Product quality and uniformity of the desired final moisture content are affected by the uneven air flow and temperature distribution inside the drying chamber. The purpose of this study is to numerically evaluate the operation parameters of a new indirect solar dryer having an appropriate design based on thermal uniformity inside the drying chamber, low construction costs and easy accessibility to resources needed for manufacture. The research was focused on both the investigation of different operation conditions and analysis of the influence of the damper position, which is incorporated into the chimney, on the internal cabinet temperature and air flow distribution. Numerical simulation was carried out with Comsol Multiphysics CFD commercial code using a reduced 2D domain model by neglecting any end effects from the side walls. The analysis of the coupled thermal-fluid model provided the velocity field, pressure distribution and temperature distribution in the solar collector and in the drying chamber when the damper was totally closed, half open and fully open and for different operation conditions. The predicted results were compared with measurements taken in-situ. With progressing computing power, it is conceivable that CFD will continue to provide explanations for more fluid flow, heat and mass transfer phenomena, leading to better equipment design and process control for the food industry.

  18. Sleep-wake profiles predict longitudinal changes in manic symptoms and memory in young people with mood disorders.

    Science.gov (United States)

    Robillard, Rébecca; Hermens, Daniel F; Lee, Rico S C; Jones, Andrew; Carpenter, Joanne S; White, Django; Naismith, Sharon L; Southan, James; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B

    2016-10-01

    Mood disorders are characterized by disabling symptoms and cognitive difficulties which may vary in intensity throughout the course of the illness. Sleep-wake cycles and circadian rhythms influence emotional regulation and cognitive functions. However, the relationships between the sleep-wake disturbances experienced commonly by people with mood disorders and the longitudinal changes in their clinical and cognitive profile are not well characterized. This study investigated associations between initial sleep-wake patterns and longitudinal changes in mood symptoms and cognitive functions in 50 young people (aged 13-33 years) with depression or bipolar disorder. Data were based on actigraphy monitoring conducted over approximately 2 weeks and clinical and neuropsychological assessment. As part of a longitudinal cohort study, these assessments were repeated after a mean follow-up interval of 18.9 months. No significant differences in longitudinal clinical changes were found between the participants with depression and those with bipolar disorder. Lower sleep efficiency was predictive of longitudinal worsening in manic symptoms (P = 0.007). Shorter total sleep time (P = 0.043) and poorer circadian rhythmicity (P = 0.045) were predictive of worsening in verbal memory. These findings suggest that some sleep-wake and circadian disturbances in young people with mood disorders may be associated with less favourable longitudinal outcomes, notably for subsequent manic symptoms and memory difficulties. © 2016 European Sleep Research Society.

  19. Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

    Science.gov (United States)

    You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

    2014-01-01

    Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

  20. Early second-trimester serum miRNA profiling predicts gestational diabetes mellitus.

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    Chun Zhao

    Full Text Available BACKGROUND: Gestational diabetes mellitus (GDM is one type of diabetes that presents during pregnancy and significantly increases the risk of a number of adverse consequences for the fetus and mother. The microRNAs (miRNA have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. However, no reported study investigates the associations between serum miRNA and GDM. METHODOLOGY/PRINCIPAL FINDINGS: We systematically used the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays to screen miRNAs in serum collected at 16-19 gestational weeks. The expression levels of three miRNAs (miR-132, miR-29a and miR-222 were significantly decreased in GDM women with respect to the controls in similar gestational weeks in our discovery evaluation and internal validation, and two miRNAs (miR-29a and miR-222 were also consistently validated in two-centric external validation sample sets. In addition, the knockdown of miR-29a could increase Insulin-induced gene 1 (Insig1 expression level and subsequently the level of Phosphoenolpyruvate Carboxy Kinase2 (PCK2 in HepG2 cell lines. CONCLUSIONS/SIGNIFICANCE: Serum miRNAs are differentially expressed between GDM women and controls and could be candidate biomarkers for predicting GDM. The utility of miR-29a, miR-222 and miR-132 as serum-based non-invasive biomarkers warrants further evaluation and optimization.

  1. Predictive potential of photoacoustic spectroscopy in breast tumor detection based on xenograft serum profiles

    Science.gov (United States)

    Priya, Mallika; Chandra, Subhas; Rao, Bola Sadashiva Satish; Ray, Satadru; Mahato, Krishna Kishore

    2015-02-01

    Breast cancer is the second most common cancer all over the world. Heterogeneity in breast cancer makes it a difficult task to detect with the existing serum markers at an early stage. With an aim to detect the disease early at the pre-malignant level, MCF-7 cells xenografts were developed using female nude mice and blood serum were extracted on days 0th, 10th, 15th & 20th post tumor cells injection (N=12 for each time point). Photoacoustic spectra were recorded on the serum samples at 281nm pulsed laser excitations. A total of 144 time domain spectra were recorded from 48 serum samples belonging to 4 different time points. These spectra were then converted into frequency domain (0-1250kHz) using MATLAB algorithms. Subsequently, seven features (mean, median, mode, variance, standard deviation, area under the curve & spectral residuals after 10th degree polynomial fit) were extracted from them and used for PCA. Further, using the first three Principal components (PCs) of the data, Linear Discriminate Analysis has been carried out. The performance of the analysis showed 82.64% accuracy in predicting various time points under study. Further, frequency-region wise analysis was also performed on the data and found 95 - 203.13 kHz region most suitable for the discrimination among the 4 time points. The analysis provided a clear discrimination in most of the spectral features under study suggesting that the photoacoustic technique has the potential to be a diagnostic tool for early detection of breast tumor development

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

    Directory of Open Access Journals (Sweden)

    Kelly A Hamby

    Full Text Available 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

  3. Computational modeling of protein mutant stability: analysis and optimization of statistical potentials and structural features reveal insights into prediction model development

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    Abhinandan Madenhalli

    2007-08-01

    Full Text Available Abstract Background Understanding and predicting protein stability upon point mutations has wide-spread importance in molecular biology. Several prediction models have been developed in the past with various algorithms. Statistical potentials are one of the widely used algorithms for the prediction of changes in stability upon point mutations. Although the methods provide flexibility and the capability to develop an accurate and reliable prediction model, it can be achieved only by the right selection of the structural factors and optimization of their parameters for the statistical potentials. In this work, we have selected five atom classification systems and compared their efficiency for the development of amino acid atom potentials. Additionally, torsion angle potentials have been optimized to include the orientation of amino acids in such a way that altered backbone conformation in different secondary structural regions can be included for the prediction model. This study also elaborates the importance of classifying the mutations according to their solvent accessibility and secondary structure specificity. The prediction efficiency has been calculated individually for the mutations in different secondary structural regions and compared. Results Results show that, in addition to using an advanced atom description, stepwise regression and selection of atoms are necessary to avoid the redundancy in atom distribution and improve the reliability of the prediction model validation. Comparing to other atom classification models, Melo-Feytmans model shows better prediction efficiency by giving a high correlation of 0.85 between experimental and theoretical ΔΔG with 84.06% of the mutations correctly predicted out of 1538 mutations. The theoretical ΔΔG values for the mutations in partially buried β-strands generated by the structural training dataset from PISCES gave a correlation of 0.84 without performing the Gaussian apodization of the

  4. Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

    Science.gov (United States)

    Brook, Anna; Wittenberg, Lea

    2015-04-01

    promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.

  5. Stabilization of resveratrol in blood circulation by conjugation to mPEG and mPEG-PLA polymers: investigation of conjugate linker and polymer composition on stability, metabolism, antioxidant activity and pharmacokinetic profile.

    Science.gov (United States)

    Siddalingappa, Basavaraj; Benson, Heather A E; Brown, David H; Batty, Kevin T; Chen, Yan

    2015-01-01

    Resveratrol is naturally occurring phytochemical with diverse biological activities such as chemoprevention, anti-inflammatory, anti-cancer, anti-oxidant. But undergoes rapid metabolism in the body (half life 0.13h). Hence Polymer conjugation utilizing different chemical linkers and polymer compositions was investigated for enhanced pharmacokinetic profile of resveratrol. Ester conjugates such as α-methoxy-ω-carboxylic acid poly(ethylene glycol) succinylamide resveratrol (MeO-PEGN-Succ-RSV) (2 and 20 kDa); MeO-PEG succinyl ester resveratrol (MeO-PEGO-Succ-RSV) (2 kDa); α-methoxy poly(ethylene glycol)-co-polylactide succinyl ester resveratrol (MeO-PEG-PLAO-Succ-RSV) (2 and 6.6kDa) were prepared by carbodiimide coupling reactions. Resveratrol-PEG ethers (2 and 5 kDa) were synthesized by alkali-mediated etherification. All polymer conjugates were fully characterized in vitro and the pharmacokinetic profile of selected conjugates was characterized in rats. Buffer and plasma stability of conjugates was dependent on polymer hydrophobicity, aggregation behavior and PEG corona, with MeO-PEG-PLAO-Succ-RSV (2 kDa) showing a 3h half-life in rat plasma in vitro. Polymer conjugates irrespective of linker chemistry protected resveratrol against metabolism in vitro. MeO-PEG-PLAO-Succ-RSV (2 kDa), Resveratrol-PEG ether (2 and 5 kDa) displayed improved pharmacokinetic profiles with significantly higher plasma area under curve (AUC), slower clearance and smaller volume of distribution, compared to resveratrol.

  6. Stabilization of resveratrol in blood circulation by conjugation to mPEG and mPEG-PLA polymers: investigation of conjugate linker and polymer composition on stability, metabolism, antioxidant activity and pharmacokinetic profile.

    Directory of Open Access Journals (Sweden)

    Basavaraj Siddalingappa

    Full Text Available Resveratrol is naturally occurring phytochemical with diverse biological activities such as chemoprevention, anti-inflammatory, anti-cancer, anti-oxidant. But undergoes rapid metabolism in the body (half life 0.13h. Hence Polymer conjugation utilizing different chemical linkers and polymer compositions was investigated for enhanced pharmacokinetic profile of resveratrol. Ester conjugates such as α-methoxy-ω-carboxylic acid poly(ethylene glycol succinylamide resveratrol (MeO-PEGN-Succ-RSV (2 and 20 kDa; MeO-PEG succinyl ester resveratrol (MeO-PEGO-Succ-RSV (2 kDa; α-methoxy poly(ethylene glycol-co-polylactide succinyl ester resveratrol (MeO-PEG-PLAO-Succ-RSV (2 and 6.6kDa were prepared by carbodiimide coupling reactions. Resveratrol-PEG ethers (2 and 5 kDa were synthesized by alkali-mediated etherification. All polymer conjugates were fully characterized in vitro and the pharmacokinetic profile of selected conjugates was characterized in rats. Buffer and plasma stability of conjugates was dependent on polymer hydrophobicity, aggregation behavior and PEG corona, with MeO-PEG-PLAO-Succ-RSV (2 kDa showing a 3h half-life in rat plasma in vitro. Polymer conjugates irrespective of linker chemistry protected resveratrol against metabolism in vitro. MeO-PEG-PLAO-Succ-RSV (2 kDa, Resveratrol-PEG ether (2 and 5 kDa displayed improved pharmacokinetic profiles with significantly higher plasma area under curve (AUC, slower clearance and smaller volume of distribution, compared to resveratrol.

  7. Stabilization of Resveratrol in Blood Circulation by Conjugation to mPEG and mPEG-PLA Polymers: Investigation of Conjugate Linker and Polymer Composition on Stability, Metabolism, Antioxidant Activity and Pharmacokinetic Profile

    Science.gov (United States)

    Siddalingappa, Basavaraj; Benson, Heather A. E.; Brown, David H.; Batty, Kevin T.; Chen, Yan

    2015-01-01

    Resveratrol is naturally occurring phytochemical with diverse biological activities such as chemoprevention, anti-inflammatory, anti-cancer, anti-oxidant. But undergoes rapid metabolism in the body (half life 0.13h). Hence Polymer conjugation utilizing different chemical linkers and polymer compositions was investigated for enhanced pharmacokinetic profile of resveratrol. Ester conjugates such as α-methoxy-ω-carboxylic acid poly(ethylene glycol) succinylamide resveratrol (MeO-PEGN-Succ-RSV) (2 and 20 kDa); MeO-PEG succinyl ester resveratrol (MeO-PEGO-Succ-RSV) (2 kDa); α-methoxy poly(ethylene glycol)-co-polylactide succinyl ester resveratrol (MeO-PEG-PLAO-Succ-RSV) (2 and 6.6kDa) were prepared by carbodiimide coupling reactions. Resveratrol-PEG ethers (2 and 5 kDa) were synthesized by alkali-mediated etherification. All polymer conjugates were fully characterized in vitro and the pharmacokinetic profile of selected conjugates was characterized in rats. Buffer and plasma stability of conjugates was dependent on polymer hydrophobicity, aggregation behavior and PEG corona, with MeO-PEG-PLAO-Succ-RSV (2 kDa) showing a 3h half-life in rat plasma in vitro. Polymer conjugates irrespective of linker chemistry protected resveratrol against metabolism in vitro. MeO-PEG-PLAO-Succ-RSV (2 kDa), Resveratrol-PEG ether (2 and 5 kDa) displayed improved pharmacokinetic profiles with significantly higher plasma area under curve (AUC), slower clearance and smaller volume of distribution, compared to resveratrol. PMID:25799413

  8. New procyanidin B3-human salivary protein complexes by mass spectrometry. Effect of salivary protein profile, tannin concentration, and time stability.

    Science.gov (United States)

    Perez-Gregorio, Maria Rosa; Mateus, Nuno; De Freitas, Victor

    2014-10-15

    Several factors could influence the tannin-protein interaction such as the human salivary protein profile, the tannin tested, and the tannin/protein ratio. The goal of this study aims to study the effect of different salivas (A, B, and C) and different tannin concentrations (0.5 and 1 mg/mL) on the interaction process as well as the complex's stability over time. This study is focused on the identification of new procyanidin B3-human salivary protein complexes. Thus, 48 major B3-human salivary protein aggregates were identified regardless of the saliva and tannin concentration tested. A higher number of aggregates was found at lower tannin concentration. Moreover, the number of protein moieties involved in the aggregation process was higher when the tannin concentration was also higher. The selectivity of the different groups of proteins to bind tannin was also confirmed. It was also verified that the B3-human salivary protein complexes formed evolved over time.

  9. Pediatric Acute-on-Chronic Liver Failure in a Specialized Liver Unit: Prevalence, Profile, Outcome, and Predictive Factors.

    Science.gov (United States)

    Alam, Seema; Lal, Bikrant B; Sood, Vikrant; Rawat, Dinesh

    2016-10-01

    The aim of the study was to assess the prevalence, profile, outcome, and predictive factors of pediatric acute-on-chronic liver failure (ACLF). All children 3 months to 18 years satisfying the Asia Pacific Association for the Study of Liver Diseases definition of ACLF were included. Data were both extracted from records (January 2011 to December 2014) and prospectively collected (January to October 2015). Successful outcome was defined as survival with native liver at 90 days, whereas poor outcome included those who died or received liver transplantation. Of the 499 children with chronic liver disease (CLD), 56 (11.2%) presented as ACLF, with a mean age of 9.35 (±4.39) years. Wilson disease and autoimmune hepatitis were the commonest underlying CLDs accounting for 24 (42.8%) and 18 (32.1%) cases, respectively. The most frequent events precipitating ACLF were a flare up of the underlying disease in 27 (48.2%) and acute viral hepatitis in 17 (30%). Poor outcome occurred in 22 (39.3%) children: 17 (30.4%) died and 5 (8.9%) received liver transplantation. Poor outcome was associated with grades 3 to 4 hepatic encephalopathy, bilirubin ≥17.5, international normalized ratio ≥3.5, and presence of 2 or more organ failures. On multivariate analysis, a Chronic Liver Failure-Sequential Organ Failure Assessment score ≥10 best predicted mortality (odds ratio 20.45, 95% confidence interval 3.9-106.7). ACLF is present in 11.2% of childhood CLD, with a 90-day native liver survival of 61%. A Chronic Liver Failure-Sequential Organ Failure Assessment score of ≥10 best predicts mortality at day 90.

  10. A health profile associated with excessive alcohol use independently predicts aortic stiffness over 10 years in black South Africans.

    Science.gov (United States)

    Maritz, Melissa; Fourie, Carla M T; van Rooyen, Johannes M; Kruger, Iolanthe M; Schutte, Aletta E

    2017-11-01

    Black populations exhibit higher arterial stiffness than whites and suffer a disproportionate burden of cardiovascular disease. It is therefore important to identify modifiable health behaviours predicting large artery stiffness in blacks. We examined whether traditional cardiovascular risk factors and health behaviours of black South Africans predict large artery stiffness 10 years later. We included 650 HIV-free participants (32.8% men) and collected data in rural and urban areas of the North West Province in 2005 and 2015. We collected questionnaire data, anthropometry, blood pressure and determined cardiometabolic and inflammatory markers from blood samples. We measured carotid-femoral pulse wave velocity (PWV) at follow-up. A total of 25.3% of our population, aged 65 ± 9.57 years, had a PWV exceeding 10 m/s. In multivariable-adjusted regression analyses, the strongest predictors of PWV were mean arterial pressure, age and heart rate (all P alcohol use (β = 0.11, P = 0.018) and plasma glucose (β = 0.08 P = 0.023) associated positively with PWV at follow-up. We found a negative association between PWV and BMI (β = -0.15, P = 0.001), and no associations with sex, smoking, inflammatory markers, lipids, liver enzymes or antihypertensive medication. When replacing self-reported alcohol with gamma-glutamyltransferase, the latter associated positively with PWV (β = 0.09, P = 0.023). A health profile associated with excessive alcohol use, including an urban setting, elevated plasma glucose and lower BMI predicts large artery stiffness independently of age and blood pressure in black South Africans over 10 years. This observation prompts urgent public health strategies to target alcohol overuse.

  11. Stability and predictive utility, over 3 years, of the illness beliefs of individuals recently diagnosed with Type 2 diabetes mellitus.

    Science.gov (United States)

    Skinner, T C; Khunti, K; Carey, M E; Dallosso, H; Heller, S; Davies, M J

    2014-10-01

    To determine the stability of beliefs of patients with Type 2 diabetes about their diabetes over 3 years, following diagnosis. Data were collected as part of a multicentre cluster randomized controlled trial of a 6-h self-management programme, across 207 general practices in the UK. Participants in the original trial were eligible for follow-up with biomedical data (HbA1c levels, blood pressure, weight, blood lipid levels) collected at the practice, and questionnaire data collected by postal distribution and return. Psychological outcome measures were depression (Hospital Anxiety and Depression Scale) and diabetes distress (Problem Areas in Diabetes scale). Illness beliefs were assessed using the Illness Perceptions Questionnaire-Revised and the Diabetes Illness Representations Questionnaire scales. At 3-year follow-up, all post-intervention differences in illness beliefs between the intervention and the control group remained significant, with perceptions of the duration of diabetes, seriousness of diabetes and perceived impact of diabetes unchanged over the course of the 3-year follow-up. The control group reported a greater understanding of diabetes during the follow-up, and the intervention group reported decreased responsibility for diabetes outcomes during the follow-up. After controlling for 4-month levels of distress and depression, the perceived impact of diabetes at 4 months remained a significant predictor of distress and depression at 3-year follow-up. Peoples' beliefs about diabetes are formed quickly after diagnosis, and thereafter seem to be relatively stable over extended follow-up. These early illness beliefs are predictive of later psychological distress, and emphasize the importance of initial context and provision of diabetes care in shaping participants' future well-being. © 2014 The Authors. Diabetic Medicine © 2014 Diabetes UK.

  12. Predicting the pKa and stability of organic acids and bases at an oil-water interface.

    Science.gov (United States)

    Andersson, M P; Olsson, M H M; Stipp, S L S

    2014-06-10

    We have used density functional theory and the implicit solvent model, COSMO-RS, to investigate how the acidity constant, pKa, of organic acids and bases adsorbed at the organic compound-aqueous solution interface changes, compared to its value in the aqueous phase. The pKa determine the surface charge density of the molecules that accumulate at the fluid-fluid interface. We have estimated the pKa by comparing the stability of the protonated and unprotonated forms of a series of molecules in the bulk aqueous solution and at an interface where parts of each molecule reside in the hydrophobic phase and the rest remains in the hydrophilic phase. We found that the pKa for acids is shifted by ∼1 pH unit to higher values compared to the bulk water pKa, whereas they are shifted to lower values by a similar amount for bases. Because this pKa shift is similar in magnitude for each of the molecules studied, we propose that the pKa for molecules at a water-organic compound interface can easily be predicted by adding a small shift to the aqueous pKa. This shift is general and correlates with the functional group. We also found that the relative composition of molecules at the fluid-fluid interface is not the same as in the bulk. For example, species such as carboxylic acids are enriched at the interface, where they can dominate surface properties, even when they are a modest component in the bulk fluid. For high surface concentrations of carboxylic acid groups at an interface, such as a self-assembled monolayer, we have demonstrated that the pKa depends on the degree of deprotonation through direct hydrogen bonding between protonated and deprotonated acidic headgroups.

  13. Investigation of abdominal muscle thickness changes after spinal manipulation in patients who meet a clinical prediction rule for lumbar stabilization.

    Science.gov (United States)

    Konitzer, Lisa N; Gill, Norman W; Koppenhaver, Shane L

    2011-09-01

    Prospective case series. To investigate changes in abdominal muscle thickness with ultrasound imaging, after spinal manipulative therapy (SMT), in a subgroup of patients with low back pain (LBP) who meet a proposed clinical prediction rule for lumbar stabilization exercise (LSE). The characteristics of a subgroup of patients with LBP who respond clinically to LSE has been proposed. Although the pathoanatomical characteristics of this subgroup have not been determined, clinicians often assume that this type of LBP is related, in part, to neuromuscular deficits of the lateral abdominal muscles. Recent evidence suggests that SMT may facilitate abdominal muscle activity and, therefore, enhance exercises targeting these deficits. Nineteen patients (mean age ± SD, 32.5 ± 7.8 years; 11 female) with LBP, who met the criteria for LSE, underwent ultrasound imaging of the transversus abdominis (TrA) and internal oblique (IO) muscles before, immediately after, and 3 to 4 days after lumbopelvic SMT. Measurements of resting thickness, contracted thickness during the abdominal drawing-in maneuver, and percent thickness change from rest to contraction of the TrA and IO muscles were analyzed with repeated-measures analysis of variance. Numeric pain rating scale and Oswestry Disability Index data were also collected. No significant differences in resting, contracted, or percent thickness change in the TrA or IO were found over the 3 time periods. There were statistically significant reductions in numeric pain rating scale and Oswestry Disability Index scores, but mean differences failed to meet the minimal clinically important difference. The results provide preliminary evidence that TrA and IO muscle resting and contracted thicknesses do not change post-SMT in patients with LBP in the LSE subgroup. In addition, while reductions in pain and disability were noted, they were not clinically meaningful.

  14. Environmental Stability of Seed Carbohydrate Profiles in Soybeans Containing Different Alleles of the Raffinose Synthase 2 (RS2) Gene.

    Science.gov (United States)

    Bilyeu, Kristin D; Wiebold, William J

    2016-02-10

    Soybean [Glycine max (L.) Merr.] is important for the high protein meal used for livestock feed formulations. Carbohydrates contribute positively or negatively to the potential metabolizable energy in soybean meal. The positive carbohydrate present in soybean meal consists primarily of sucrose, whereas the negative carbohydrate components are the raffinose family of oligosaccharides (RFOs), raffinose and stachyose. Increasing sucrose and decreasing raffinose and stachyose are critical targets to improve soybean. In three recently characterized lines, variant alleles of the soybean raffinose synthase 2 (RS2) gene were associated with increased sucrose and decreased RFOs. The objective of this research was to compare the environmental stability of seed carbohydrates in soybean lines containing wild-type or variant alleles of RS2 utilizing a field location study and a date of planting study. The results define the carbohydrate variation in distinct regional and temporal environments using soybean lines with different alleles of the RS2 gene.

  15. Profiling crop pollinators: life history traits predict habitat use and crop visitation by Mediterranean wild bees.

    Science.gov (United States)

    Pisanty, Gideon; Mandelik, Yael

    2015-04-01

    Wild pollinators, bees in particular, may greatly contribute to crop pollination and provide a safety net against declines in commercial pollinators. However, the identity, life history traits, and environmental sensitivities of main crop pollinator species.have received limited attention. These are crucial for predicting pollination services of different communities and for developing management practices that enhance crop pollinators. We sampled wild bees in three crop systems (almond, confection sunflower, and seed watermelon) in a mosaic Israeli Mediterranean landscape. Bees were sampled in field/orchard edges and interiors, and in seminatural scrub surrounding the fields/orchards. We also analyzed land cover at 50-2500 m radii around fields/orchards. We used this data to distinguish crop from non-crop pollinators based on a set of life history traits (nesting, lecty, sociality, body size) linked to habitat preference and crop visitation. Bee abundance and species richness decreased from the surrounding seminatural habitat to the field/orchard interior, especially across the seminatural habitat-field edge ecotone. Thus, although rich bee communities were found near fields, only small fractions crossed the ecotone and visited crop flowers in substantial numbers. The bee assemblage in agricultural fields/orchards and on crop flowers was dominated by ground-nesting bees of the tribe Halictini, which tend to nest within fields. Bees' habitat preferences were determined mainly by nesting guild, whereas crop visitation was determined mainly by sociality. Lecty and body size also affected both measures. The percentage of surrounding seminatural habitat at 250-2500 m radii had a positive effect on wild bee diversity in field edges, for all bee guilds, while at 50-100 m radii, only aboveground nesters were positively affected. In sum, we found that crop and non-crop pollinators are distinguished by behavioral and morphological traits. Hence, analysis of life

  16. Relationship between the prognostic and predictive value of the intrinsic subtypes and a validated gene profile predictive of loco-regional control and benefit from post-mastectomy radiotherapy in patients with high-risk breast cancer.

    Science.gov (United States)

    Tramm, Trine; Kyndi, Marianne; Myhre, Simen; Nord, Silje; Alsner, Jan; Sørensen, Flemming Brandt; Sørlie, Therese; Overgaard, Jens

    2014-10-01

    Breast cancer is characterized by great molecular heterogeneity demonstrated, e.g. by the intrinsic subtypes. Administration of post-mastectomy radiotherapy (PMRT) does, however, not reflect this heterogeneity. A gene profile (DBCG-RT profile) has recently been developed and validated, and has shown prognostic impact in terms of loco-regional failure and predictive impact for PMRT. Reports have also shown predictive value in terms of benefit of PMRT from intrinsic subtypes and derived approximations. The aim of this study was to examine: 1) the agreement between various methods for determining the intrinsic subtypes; and 2) the relationship between the prognostic and predictive impact of the DBCG-RT profile and the intrinsic subtypes. Intrinsic subtypes and the DBCG-RT profile was determined from microarray analysis based on fresh frozen tissue from 191 patients included in the Danish Breast Cancer Cooperative Group (DBCG) 82bc trial. Corresponding formalin-fixed, paraffin-embedded tissue was available from 146 of these patients and from another 890 DBCG82bc patients. Estrogen receptor, progesterone receptor, HER2, CK5/6, Ki-67 and EGFR were combined into immunohistochemical approximations of the intrinsic subtypes. Endpoint considered was loco-regional recurrence (LRR). The DBCG-RT profile identified a group of patients with low risk of LRR and no additional benefit from PMRT among all subtypes. Combining six immunohistochemical markers identified a subgroup of triple negative patients with high risk of LRR and significant benefit from PMRT. Agreement in the different assignments of tumors to the subtypes was suboptimal, and the clinical outcome and predicted benefit from PMRT varied according to the method used for assignment. The prognostic and predictive information obtained from the DBCG-RT profile cannot be substituted by any approximation of the tumors intrinsic subtype. The predictive value of the intrinsic subtypes in terms of PMRT was influenced by the

  17. Large Eddy Simulation of Single Element Gas Centered Swirl Coaxial Injectors for Combustion Stability Prediction (Conference Paper with Briefing Charts)

    Science.gov (United States)

    2017-07-10

    Engineer, AIAA Member 2 Research Aerospace Engineer, AIAA Member 3 Senior Aerospace Engineer, AIAA Senior Member 4 Senior Scientist, AIAA Senior...velocity profile . The addition of this profile results in a momentum magnitude equal to the experimental momentum. A supersonic outflow condition is...July, AIAA Paper No. 2705862, 2017. [8] S. Schumaker, S. Danczyk, and M. Lightfoot, “Effect of Cup Length on Film Profiles in Gas-Centered Swirl

  18. Evaluation of the release profile, stability and antioxidant activity of a proanthocyanidin-rich cinnamon (Cinnamomum zeylanicum) extract co-encapsulated with α-tocopherol by spray chilling.

    Science.gov (United States)

    Tulini, Fabrício L; Souza, Volnei B; Thomazini, Marcelo; Silva, Marluci P; Massarioli, Adna P; Alencar, Severino M; Pallone, Eliria M J A; Genovese, Maria I; Favaro-Trindade, Carmen S

    2017-05-01

    Cinnamon has many health improving compounds such as proanthocyanidins, which also have potential for the prevention of damages caused by diabetes. Similarly, α-tocopherol is a natural antioxidant with important role on protection of fatty acids in membranes and lipoproteins. However, the addition of antioxidants in food may result in interaction with food matrix, low stability and unpleasant taste. In the present study, a proanthocyanidin-rich cinnamon extract (PRCE) (Cinnamomum zeylanicum) was co-encapsulated with α-tocopherol into solid lipid microparticles (SLMs) by spray chilling. The microparticles were characterized with regard to the physical and chemical properties, morphology, proanthocyanidin stability and release profile. SLMs were spherical with an average diameter of ca. 80μm. Proanthocyanidins were highly stable in SLMs stored for up to 90days at 5, 25 and 37°C. Moreover, SLMs gradually released proanthocyanidins in simulated gastrointestinal fluids by a diffusional process, following a Korsmeyer-Peppas kinetic. Analyses of the antioxidant compounds indicated that PRCE components exhibited a higher scavenging capacity against reactive oxygen species (ROS) and reactive nitrogen species (RNS). Thus, the SLMs produced in the present study have potential for application in the development of new functional foods and nutraceuticals, also providing an alternative for the controlled release of proanthocyanidins and α-tocopherol into the intestine. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated With Oxidation and Interdiffusion of Overlay-Coated Substrates

    Science.gov (United States)

    Nesbitt, James A.

    2001-01-01

    A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating life based on a concentration dependent failure criterion (e.g., surface solute content drops to 2%). The computer code is written in FORTRAN and employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

  20. Rapid method to predict the storage stability of middle distillates; Schnelltest zur Vorhersage der Lagerstabilitaet von Mitteldestillaten

    Energy Technology Data Exchange (ETDEWEB)

    Depta, H.; Wehn, R. [RWE - Gesellschaft fuer Forschung und Entwicklung mbH, Wesseling (Germany); Kohlmeyer, U. [Deutsche Shell AG, Hamburg (Germany)

    1998-12-01

    In the literature, various quick tests to predict the ageing stability of middle distillates are described. 59 gasoil components and finished products were tested, using methods recommended by a detailed literature study DGMK-Report 484, namely: - the colorimetric/spectrophotometric method according to R.K. Solly and S.J. Marshman, - the quantification of Soluble Macromolecular Oxidatively Reactive Species (SMORS) according to M.A. Wechter and D.R. Hardy, - the determination of phenalene and phenalenone as well as non-basic nitrogenous aromatics. ASTM D 4625-92 was used as a reference test (storage at 43 C over a period of 12 weeks, with air contact). The results obtained showed that none of the methods mentioned above are suitable as a reliable quick test, because the regression analysis shows no acceptable correlation between the data obtained and the insolubles derived from the reference test. The hypothesis of Pedley et al., referring to the ageing mechanism of middle distillates, could not be confirmed. The spectrophotometric method gives the best result, considering the total nitrogen content. The accuracy of the prediction of ASTM-Test results is about 75%. The additionally carried out `Rancimat-Test` does not correlate at all with the insolubles based on ASTM D 4625-92. The insolubles as determined according to ASTM D 4625 neither do correlate with the amount of sediments which are formed after one year`s storage under genuine conditions. On the other hand, the supplementarily conducted `Shell Window Test` allows a prediction of the longterm storage behaviour with a likelihood of 78% which is expected to improve after a revision of the method with regard to reproducible test conditions. (orig.) [Deutsch] In der Literatur werden verschiedene Schnelltests zur Vorhersage der Alterungsstabilitaet von Mitteldestillaten beschrieben. An 59 Gasoel-Komponenten und -Fertigprodukten wurden die in der Literaturrecherche DGMK-Bericht 484 empfohlenen Methoden ueberprueft

  1. Prediction of in-vivo pharmacokinetic profile for immediate and modified release oral dosage forms of furosemide using an in-vitro-in-silico-in-vivo approach.

    Science.gov (United States)

    Otsuka, Keiichi; Wagner, Christian; Selen, Arzu; Dressman, Jennifer

    2015-05-01

    To develop a physiologically based pharmacokinetic (PBPK) model for furosemide immediate release (IR) tablets and modified release (MR) capsules by coupling biorelevant dissolution testing results with pharmacokinetic (PK) and physiologic parameters, and to investigate the key factors influencing furosemide absorption using simulation approaches and the PBPK model. Using solubility, dissolution kinetics, gastrointestinal (GI) parameters and disposition parameters, a PBPK model for furosemide was developed with STELLA software. Solubility and dissolution profiles for both formulations were evaluated in biorelevant and compendial media. The simulated plasma profiles were compared with in-vivo profiles using point estimates of area under plasma concentration-time curve, maximal concentration after the dose and time to maximal concentration after the dose. Simulated plasma profiles of both furosemide IR tablets and MR capsules were similar to the observed in-vivo profile in terms of PK parameters. Sensitivity analysis of the IR tablet model indicated that both the gastric emptying and absorption rate have an influence on the plasma profile. For the MR capsules, the sensitivity analysis suggested that the release rate in the small intestine, gastric emptying and the absorption rate all have an influence on the plasma profile. A predictive model to describe both IR and MR dosage forms containing furosemide was attained. Because sensitivity analysis of the model is able to identify key factors influencing the plasma profile, this in-vitro-in-silico-in-vivo approach could be a useful tool for facilitating formulation development of drug products. © 2015 Royal Pharmaceutical Society.

  2. Development of a Multivariate Predictive Model to Estimate Ionized Calcium Concentration from Serum Biochemical Profile Results in Dogs.

    Science.gov (United States)

    Danner, J; Ridgway, M D; Rubin, S I; Le Boedec, K

    2017-09-01

    Ionized calcium concentration is the gold standard to assess calcium status in dogs, but measurement is not always available. (1) To predict ionized calcium concentration from biochemical results and compare the diagnostic performance of predicted ionized calcium concentration (piCa) to those of total calcium concentration (tCa) and 2 corrected tCa formulas; and (2) to study the relationship between biochemical results and variation of measured ionized calcium concentration (miCa). A total of 1,719 dogs with both miCa and biochemical profile results available. Cross-sectional study. Using 1,200 dogs, piCa was determined using a multivariate adaptive regression splines model. Its accuracy and performance were tested on the remaining 519 dogs. The final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Measured ionized calcium concentration was better correlated with piCa than with tCa and corrected tCa and had higher overall diagnostic accuracy to diagnose hypocalcemia and hypercalcemia, but not significantly for hypercalcemia. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) and as specific (98.4%) as tCa. Positive and negative predictive values of piCa were high for both hypercalcemia (90% and 98%, respectively) and hypocalcemia (70.8% and 87.7%, respectively). Predicted ionized calcium concentration can be obtained from readily available biochemical and patient results and seems more useful than tCa and corrected tCa to assess calcium disorders in dogs when miCa is unavailable. Validation on external data, however, is warranted. Copyright © 2017 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

  3. Numerical Stability and Control Analysis Towards Falling-Leaf Prediction Capabilities of Splitflow for Two Generic High-Performance Aircraft Models

    Science.gov (United States)

    Charlton, Eric F.

    1998-01-01

    Aerodynamic analysis are performed using the Lockheed-Martin Tactical Aircraft Systems (LMTAS) Splitflow computational fluid dynamics code to investigate the computational prediction capabilities for vortex-dominated flow fields of two different tailless aircraft models at large angles of attack and sideslip. These computations are performed with the goal of providing useful stability and control data to designers of high performance aircraft. Appropriate metrics for accuracy, time, and ease of use are determined in consultations with both the LMTAS Advanced Design and Stability and Control groups. Results are obtained and compared to wind-tunnel data for all six components of forces and moments. Moment data is combined to form a "falling leaf" stability analysis. Finally, a handful of viscous simulations were also performed to further investigate nonlinearities and possible viscous effects in the differences between the accumulated inviscid computational and experimental data.

  4. Long-term skeletal and profile stability after surgical-orthodontic treatment of Class II and Class III malocclusion.

    Science.gov (United States)

    de Lir, Ana de Lourdes Sá; de Moura, Walter Leal; Oliveira Ruellas, Antonio Carlos; Gomes Souza, Margareth Maria; Nojima, Lincoln Issamu

    2013-06-01

    The purpose of this perspective research was to study the long-term stability of skeletal, dentoalveolar and soft tissue after orthognathic surgery in subjects presenting with Class II and Class III malocclusions. The available digitized cephalometric radiographs, including pretreatment (t0), presurgery (t1), a minimum of 12 months postsurgery (t2) and at least 3 years after the orthosurgery treatment (t3) were taken between 1998 and 2010. In Group 1 mandibular advancement and in Group 2 mandibular advancement and maxillary impaction surgery were performed for correction of Class II. In Group 3 maxillary advancement and in Group 4 surgical maxillary advancement with mandibular setback, for correction of Class III. In all the phases mandibular length was shorter in Group 1, and the inferior third of the face was longer in Group 2. Before the surgery there was greater maxillary deficiency in Group 3 than Group 4 and mandibular length was longer in Group 4. In Groups 1 and 2, at retention phase, relapse occurred due to the increase in mandibular plane, whereas the surgeries performed in Groups 3 and 4 remained stable. Copyright © 2012 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  5. Predicting effective pro-apoptotic anti-leukaemic drug combinations using co-operative dynamic BH3 profiling.

    Directory of Open Access Journals (Sweden)

    Martin Grundy

    Full Text Available The BH3-only apoptosis agonists BAD and NOXA target BCL-2 and MCL-1 respectively and co-operate to induce apoptosis. On this basis, therapeutic drugs targeting BCL-2 and MCL-1 might have enhanced activity if used in combination. We identified anti-leukaemic drugs sensitising to BCL-2 antagonism and drugs sensitising to MCL-1 antagonism using the technique of dynamic BH3 profiling, whereby cells were primed with drugs to discover whether this would elicit mitochondrial outer membrane permeabilisation in response to BCL-2-targeting BAD-BH3 peptide or MCL-1-targeting MS1-BH3 peptide. We found that a broad range of anti-leukaemic agents-notably MCL-1 inhibitors, DNA damaging agents and FLT3 inhibitors-sensitise leukaemia cells to BAD-BH3. We further analysed the BCL-2 inhibitors ABT-199 and JQ1, the MCL-1 inhibitors pladienolide B and torin1, the FLT3 inhibitor AC220 and the DNA double-strand break inducer etoposide to correlate priming responses with co-operative induction of apoptosis. ABT-199 in combination with pladienolide B, torin1, etoposide or AC220 strongly induced apoptosis within 4 hours, but the MCL-1 inhibitors did not co-operate with etoposide or AC220. In keeping with the long half-life of BCL-2, the BET domain inhibitor JQ1 was found to downregulate BCL-2 and to prime cells to respond to MS1-BH3 at 48, but not at 4 hours: prolonged priming with JQ1 was then shown to induce rapid cytochrome C release when pladienolide B, torin1, etoposide or AC220 were added. In conclusion, dynamic BH3 profiling is a useful mechanism-based tool for understanding and predicting co-operative lethality between drugs sensitising to BCL-2 antagonism and drugs sensitising to MCL-1 antagonism. A plethora of agents sensitised cells to BAD-BH3-mediated mitochondrial outer membrane permeabilisation in the dynamic BH3 profiling assay and this was associated with effective co-operation with the BCL-2 inhibitory compounds ABT-199 or JQ1.

  6. Prediction of overall in vitro microsomal stability of drug candidates based on molecular modeling and support vector machines. Case study of novel arylpiperazines derivatives.

    Directory of Open Access Journals (Sweden)

    Szymon Ulenberg

    Full Text Available Other than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model and predict metabolic stability quantitatively is still lacking. This study proposes a workflow for developing quantitative metabolic stability-structure relationships, taking a set of 30 arylpiperazine derivatives as an example. The metabolic stability of the compounds was assessed in in vitro incubations in the presence of human liver microsomes and NADPH and subsequently quantified by liquid chromatography-mass spectrometry (LC-MS. Density functional theory (DFT calculations were used to obtain 30 models of the molecules, and Dragon software served as a source of structure-based molecular descriptors. For modeling structure-metabolic stability relationships, Support Vector Machines (SVM, a non-linear machine learning technique, were found to be more effective than a regression technique, based on the validation parameters obtained. Moreover, for the first time, general sites of metabolism for arylpiperazines bearing the 4-aryl-2H-pyrido[1,2-c]pyrimidine-1,3-dione system were defined by analysis of Q-TOF-MS/MS spectra. The results indicated that the application of one of the most advanced chemometric techniques combined with a simple and quick in vitro procedure and LC-MS analysis provides a novel and valuable tool for predicting metabolic half-life values. Given the reduced time and simplicity of analysis, together with the accuracy of the predictions obtained, this is a valid approach for predicting metabolic stability using structural data. The approach presented provides a novel, comprehensive and reliable tool

  7. Comparisons of refractive index gradient and stability profiles measured by balloons and the MU radar at a high vertical resolution in the lower stratosphere

    Directory of Open Access Journals (Sweden)

    H. Luce

    2007-02-01

    Full Text Available Many experimental studies have demonstrated that VHF Stratosphere-Troposphere (ST radar echo power is proportional to the generalized refractive index gradient squared M2 when using a vertically oriented beam. Because humidity is generally negligible above the tropopause, VHF ST radars can thus provide information on the static stability (quantified by the squared Brunt-Väisälä frequency N2 at stratospheric heights and this capability is useful for many scientific applications. Most studies have been performed until now at a vertical resolution of 150 m or more. In the present paper, results of comparisons between radar- and (balloon borne radiosonde-derived M2 and N2 are shown at a better vertical resolution of 50 m with the MU radar (34.85° N, 136.15° E; Japan by benefiting from the range resolution improvement provided by the multi-frequency range imaging technique, using the Capon processing method. Owing to favorable winds in the troposphere, the radiosondes did not drift horizontally more than about 30 km from the MU radar site by the time they reached an altitude of 20 km. The measurements were thus simultaneous and almost collocated. Very good agreements have been obtained between both high resolution profiles of M2, as well as profiles of N2. It is also shown that this agreement can still be improved by taking into account a frozen-in advection of the air parcels by a horizontally uniform wind. Therefore, it can be concluded that 1 the range imaging technique with the Capon method really provides substantial range resolution improvement, despite the relatively weak Signal-to-Noise Ratios (SNR over the analyzed region of the lower stratosphere, 2 the proportionality of the radar echo power to M2 at a vertical scale down to 50 m in the lower stratosphere is experimentally demonstrated, 3 the MU radar can provide stability profiles with a vertical resolution of 50 m at heights where humidity is negligible, 4 stable stratospheric

  8. Comparisons of refractive index gradient and stability profiles measured by balloons and the MU radar at a high vertical resolution in the lower stratosphere

    Directory of Open Access Journals (Sweden)

    H. Luce

    2007-02-01

    Full Text Available Many experimental studies have demonstrated that VHF Stratosphere-Troposphere (ST radar echo power is proportional to the generalized refractive index gradient squared M2 when using a vertically oriented beam. Because humidity is generally negligible above the tropopause, VHF ST radars can thus provide information on the static stability (quantified by the squared Brunt-Väisälä frequency N2 at stratospheric heights and this capability is useful for many scientific applications. Most studies have been performed until now at a vertical resolution of 150 m or more. In the present paper, results of comparisons between radar- and (balloon borne radiosonde-derived M2 and N2 are shown at a better vertical resolution of 50 m with the MU radar (34.85° N, 136.15° E; Japan by benefiting from the range resolution improvement provided by the multi-frequency range imaging technique, using the Capon processing method. Owing to favorable winds in the troposphere, the radiosondes did not drift horizontally more than about 30 km from the MU radar site by the time they reached an altitude of 20 km. The measurements were thus simultaneous and almost collocated. Very good agreements have been obtained between both high resolution profiles of M2, as well as profiles of N2. It is also shown that this agreement can still be improved by taking into account a frozen-in advection of the air parcels by a horizontally uniform wind. Therefore, it can be concluded that 1 the range imaging technique with the Capon method really provides substantial range resolution improvement, despite the relatively weak Signal-to-Noise Ratios (SNR over the analyzed region of the lower stratosphere, 2 the proportionality of the radar echo power to M2 at a vertical scale down to 50 m in the lower stratosphere is experimentally demonstrated, 3 the MU radar can

  9. Evaluation of Uterine Biophysical Profile and to Assess its Role in Predicting Conception among Unexplained Primary Infertility Patients

    Directory of Open Access Journals (Sweden)

    Pooja Gupta

    2014-12-01

    Full Text Available Introduction: Infertility is a devastating disease which affects its victims at a very basic level the ability to reproduce. This can be divisive to the couples involved, their relatives and friends. The influence of infertility can be immense. There are a lot of medical and social consequences of infertility and the psychological sequelae are one of them. Affected patients and their families suffer from loss of esteem, disappointment and depression. Considering the immense effect of infertility on the life of not only the affected couples but also on their families and relatives the present study was conducted with following objective. Objective: To evaluate the Uterine Biophysical Profile and to assess its role in predicting the conception outcome in spontaneous cycles in patients with unexplained primary infertility. Material &Methods: A prospective observational study was conducted in the Department of Obstetrics and Gynaecology, U.P. Rural Institute of Medical Sciences & Research, Saifaion 55 women with unexplained primary infertility after standard diagnostic work up. Ultrasound (TVS measurement of all patients was performed in their midcycle of spontaneous cycle. The Uterine Biophysical Profile (UBP i.e. certain sonographic qualities of the uterus were noted during the normal mid-cycle of these patients. These included 7 parameters: Endometrial thickness in greatest AP dimension of 7 mm or greater (full-thickness measurement, a layered ("5 line" appearance to the endometrium, myometrial contractions causing a wave like motion of the endometrium, homogeneous myometrial echogenicity, uterine artery blood flow (as measured by PI, less than 3.0, blood flow within zone 3 using color doppler technique, myometrial blood flow seen on gray-scale examination. The Uterine Scoring System for Reproduction ("USSR" was used to evaluate the total score. Results: Among 55 unexplained primary infertility patients 24 i.e. 43.63% conceived by serial

  10. High Pressure Homogenization of Porcine Pepsin Protease: Effects on Enzyme Activity, Stability, Milk Coagulation Profile and Gel Development.

    Directory of Open Access Journals (Sweden)

    Bruno Ricardo de Castro Leite Júnior

    Full Text Available This study investigated the effect of high pressure homogenization (HPH (up to 190 MPa on porcine pepsin (proteolytic and milk-clotting activities, and the consequences of using the processed enzyme in milk coagulation and gel formation (rheological profile, proteolysis, syneresis, and microstructure. Although the proteolytic activity (PA was not altered immediately after the HPH process, it reduced during enzyme storage, with a 5% decrease after 60 days of storage for samples obtained with the enzyme processed at 50, 100 and 150 MPa. HPH increased the milk-clotting activity (MCA of the enzyme processed at 150 MPa, being 15% higher than the MCA of non-processed samples after 60 days of storage. The enzyme processed at 150 MPa produced faster aggregation and a more consistent milk gel (G' value 92% higher after 90 minutes when compared with the non-processed enzyme. In addition, the gels produced with the enzyme processed at 150 MPa showed greater syneresis after 40 minutes of coagulation (forming a more compact protein network and lower porosity (evidenced by confocal microscopy. These effects on the milk gel can be associated with the increment in MCA and reduction in PA caused by the effects of HPH on pepsin during storage. According to the results, HPH stands out as a process capable of changing the proteolytic characteristics of porcine pepsin, with improvements on the milk coagulation step and gel characteristics. Therefore, the porcine pepsin submitted to HPH process can be a suitable alternative for the production of cheese.

  11. High Pressure Homogenization of Porcine Pepsin Protease: Effects on Enzyme Activity, Stability, Milk Coagulation Profile and Gel Development.

    Science.gov (United States)

    Leite Júnior, Bruno Ricardo de Castro; Tribst, Alline Artigiani Lima; Cristianini, Marcelo

    2015-01-01

    This study investigated the effect of high pressure homogenization (HPH) (up to 190 MPa) on porcine pepsin (proteolytic and milk-clotting activities), and the consequences of using the processed enzyme in milk coagulation and gel formation (rheological profile, proteolysis, syneresis, and microstructure). Although the proteolytic activity (PA) was not altered immediately after the HPH process, it reduced during enzyme storage, with a 5% decrease after 60 days of storage for samples obtained with the enzyme processed at 50, 100 and 150 MPa. HPH increased the milk-clotting activity (MCA) of the enzyme processed at 150 MPa, being 15% higher than the MCA of non-processed samples after 60 days of storage. The enzyme processed at 150 MPa produced faster aggregation and a more consistent milk gel (G' value 92% higher after 90 minutes) when compared with the non-processed enzyme. In addition, the gels produced with the enzyme processed at 150 MPa showed greater syneresis after 40 minutes of coagulation (forming a more compact protein network) and lower porosity (evidenced by confocal microscopy). These effects on the milk gel can be associated with the increment in MCA and reduction in PA caused by the effects of HPH on pepsin during storage. According to the results, HPH stands out as a process capable of changing the proteolytic characteristics of porcine pepsin, with improvements on the milk coagulation step and gel characteristics. Therefore, the porcine pepsin submitted to HPH process can be a suitable alternative for the production of cheese.

  12. Electrostatic contribution of surface charge residues to the stability of a thermophilic protein: benchmarking experimental and predicted pKa values.

    Directory of Open Access Journals (Sweden)

    Chi-Ho Chan

    Full Text Available Optimization of the surface charges is a promising strategy for increasing thermostability of proteins. Electrostatic contribution of ionizable groups to the protein stability can be estimated from the differences between the pKa values in the folded and unfolded states of a protein. Using this pKa-shift approach, we experimentally measured the electrostatic contribution of all aspartate and glutamate residues to the stability of a thermophilic ribosomal protein L30e from Thermococcus celer. The pKa values in the unfolded state were found to be similar to model compound pKas. The pKa values in both the folded and unfolded states obtained at 298 and 333 K were similar, suggesting that electrostatic contribution of ionizable groups to the protein stability were insensitive to temperature changes. The experimental pKa values for the L30e protein in the folded state were used as a benchmark to test the robustness of pKa prediction by various computational methods such as H++, MCCE, MEAD, pKD, PropKa, and UHBD. Although the predicted pKa values were affected by crystal contacts that may alter the side-chain conformation of surface charged residues, most computational methods performed well, with correlation coefficients between experimental and calculated pKa values ranging from 0.49 to 0.91 (p<0.01. The changes in protein stability derived from the experimental pKa-shift approach correlate well (r = 0.81 with those obtained from stability measurements of charge-to-alanine substituted variants of the L30e protein. Our results demonstrate that the knowledge of the pKa values in the folded state provides sufficient rationale for the redesign of protein surface charges leading to improved protein stability.

  13. Maximum predictive power of the microarray-based models for clinical outcomes is limited by correlation between endpoint and gene expression profile.

    Science.gov (United States)

    Zhao, Chen; Shi, Leming; Tong, Weida; Shaughnessy, John D; Oberthuer, André; Pusztai, Lajos; Deng, Youping; Symmans, W Fraser; Shi, Tieliu

    2011-12-23

    Microarray data have been used for gene signature selection to predict clinical outcomes. Many studies have attempted to identify factors that affect models' performance with only little success. Fine-tuning of model parameters and optimizing each step of the modeling process often results in over-fitting problems without improving performance. We propose a quantitative measurement, termed consistency degree, to detect the correlation between disease endpoint and gene expression profile. Different endpoints were shown to have different consistency degrees to gene expression profiles. The validity of this measurement to estimate the consistency was tested with significance at a p-value less than 2.2e-16 for all of the studied endpoints. According to the consistency degree score, overall survival milestone outcome of multiple myeloma was proposed to extend from 730 days to 1561 days, which is more consistent with gene expression profile. For various clinical endpoints, the maximum predictive powers of different microarray-based models are limited by the correlation between endpoint and gene expression profile of disease samples as indicated by the consistency degree score. In addition, previous defined clinical outcomes can also be reassessed and refined more coherent according to related disease gene expression profile. Our findings point to an entirely new direction for assessing the microarray-based predictive models and provide important information to gene signature based clinical applications.

  14. Personality predictors of successful development: toddler temperament and adolescent personality traits predict well-being and career stability in middle adulthood.

    Directory of Open Access Journals (Sweden)

    Marek Blatný

    Full Text Available The aim of the study was to predict both adaptive psychological functioning (well-being and adaptive social functioning (career stability in middle adulthood based on behaviors observed in toddlerhood and personality traits measured in adolescence. 83 people participated in an ongoing longitudinal study started in 1961 (58% women. Based on children's behavior in toddlerhood, three temperamental dimensions were identified - positive affectivity, negative affectivity and disinhibition. In adolescence, extraversion and neuroticism were measured at the age of 16 years. Various aspects of well-being were used as indicators of adaptive psychological functioning in adulthood: life satisfaction, self-esteem and self-efficacy. Career stability was used as an indicator of adaptive social functioning. Job careers of respondents were characterized as stable, unstable or changeable. Extraversion measured at the age of 16 proved to be the best predictor of well-being indicators; in case of self-efficacy it was also childhood disinhibition. Extraversion in adolescence, childhood disinhibition and negative affectivity predicted career stability. Findings are discussed in the context of a theoretical framework of higher order factors of the Big Five personality constructs, stability and plasticity.

  15. Personality Predictors of Successful Development: Toddler Temperament and Adolescent Personality Traits Predict Well-Being and Career Stability in Middle Adulthood

    Science.gov (United States)

    2015-01-01

    The aim of the study was to predict both adaptive psychological functioning (well-being) and adaptive social functioning (career stability) in middle adulthood based on behaviors observed in toddlerhood and personality traits measured in adolescence. 83 people participated in an ongoing longitudinal study started in 1961 (58% women). Based on children’s behavior in toddlerhood, three temperamental dimensions were identified – positive affectivity, negative affectivity and disinhibition. In adolescence, extraversion and neuroticism were measured at the age of 16 years. Various aspects of well-being were used as indicators of adaptive psychological functioning in adulthood: life satisfaction, self-esteem and self-efficacy. Career stability was used as an indicator of adaptive social functioning. Job careers of respondents were characterized as stable, unstable or changeable. Extraversion measured at the age of 16 proved to be the best predictor of well-being indicators; in case of self-efficacy it was also childhood disinhibition. Extraversion in adolescence, childhood disinhibition and negative affectivity predicted career stability. Findings are discussed in the context of a theoretical framework of higher order factors of the Big Five personality constructs, stability and plasticity. PMID:25919394

  16. Prediction of pH-Dependent Hydrophobic Profiles of Small Molecules from Miertus-Scrocco-Tomasi Continuum Solvation Calculations.

    Science.gov (United States)

    Zamora, William J; Curutchet, Carles; Campanera, Josep M; Luque, F Javier

    2017-10-26

    Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (PN) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log PN values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (PI). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.

  17. The Janus-faced nature of time spent on homework : Using latent profile analyses to predict academic achievement over a school year

    NARCIS (Netherlands)

    Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge

    2015-01-01

    Homework time and achievement are only modestly associated, whereas homework effort has consistently been shown to positively predict later achievement. We argue that time spent on homework can be an important predictor of achievement when combined with measures of homework effort. Latent profile

  18. Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

    Energy Technology Data Exchange (ETDEWEB)

    Hadhri, Mahdi; Ouafi, Abderazzak El; Barka, Noureddine [University of Quebec, Rimouski (Canada)

    2017-02-15

    This paper presents a comprehensive approach developed to design an effective prediction model for hardness profile in laser surface transformation hardening process. Based on finite element method and Artificial neural networks, the proposed approach is built progressively by (i) examining the laser hardening parameters and conditions known to have an influence on the hardened surface attributes through a structured experimental investigation, (ii) investigating the laser hardening parameters effects on the hardness profile through extensive 3D modeling and simulation efforts and (ii) integrating the hardening process parameters via neural network model for hardness profile prediction. The experimental validation conducted on AISI4340 steel using a commercial 3 kW Nd:Yag laser, confirm the feasibility and efficiency of the proposed approach leading to an accurate and reliable hardness profile prediction model. With a maximum relative error of about 10 % under various practical conditions, the predictive model can be considered as effective especially in the case of a relatively complex system such as laser surface transformation hardening process.

  19. Validation of a BMI cut-off point to predict an adverse cardiometabolic profile with adiposity measurements by dual-energy X-ray absorptiometry in Guatemalan children.

    Science.gov (United States)

    Redondo, Olga; Villamor, Eduardo; Valdés, Javiera; Bilal, Usama; Caballero, Benjamín; Roche, Dina; Kroker, Fernanda; Ramírez-Zea, Manuel; Franco, Manuel

    2015-04-01

    To identify a body fat percentage (%BF) threshold related to an adverse cardiometabolic profile and its surrogate BMI cut-off point. Cross-sectional study. Two public schools in poor urban areas on the outskirts of Guatemala City. A convenience sample of ninety-three healthy, prepubertal, Ladino children (aged 7-12 years). Spearman correlations of cardiometabolic parameters were higher with %BF than with BMI-for-age Z-score. BMI-for-age Z-score and %BF were highly correlated (r=0·84). The %BF threshold that maximized sensitivity and specificity for predicting an adverse cardiometabolic profile (elevated homeostasis model assessment-insulin resistance index and/or total cholesterol:HDL-cholesterol ratio) according to receiver operating characteristic curve analysis was 36 %. The BMI-for-age Z-score cut-off point that maximized the prediction of BF ≥ 36 % by the same procedure was 1·5. The area under the curve (AUC) for %BF and for BMI data showed excellent accuracy to predict an adverse cardiometabolic profile (AUC 0·93 (sd 0·04)) and excess adiposity (AUC 0·95 (sd 0·02)). Since BMI standards have limitations in screening for adiposity, specific cut-off points based on ethnic-/sex- and age-specific %BF thresholds are needed to better predict an adverse cardiometabolic profile.

  20. Effect of whole wheat flour on the quality, texture profile, and oxidation stability of instant fried noodles.

    Science.gov (United States)

    Cao, Xinlei; Zhou, Sumei; Yi, Cuiping; Wang, Li; Qian, Haifeng; Zhang, Hui; Qi, Xiguang

    2017-05-04

    The effects of whole wheat flour (WWF) on pasting properties of instant fried noodle dry mix and quality of final product were investigated in this research. Refined wheat flour in the recipe for instant-fried noodle was replaced by WWF at different levels. The peak and final viscosities were significantly and negatively correlated to WWF substitution level. With increasing WWF level, the hardness, cohesiveness, adhesiveness, and resilience values of instant fried noodles decreased by 11.63, 16.23, 16.67, 20.00%, respectively. WWF darkened noodle's surface color and increased its oil content (26.63%). A porous and less uniformed structure of the WWF instant fried noodles was observed by a scanning electron microscope. Moreover, the WWF incorporation lowered peroxide values of the instant fried noodles during storage. In conclusion, even though the oil content increased, WWF was helpful to inhibit the oil oxidation and produce instant fried noodles with softer texture and less sticky surface. Refined wheat flour in the recipe for instant-fried noodle was replaced by whole wheat flour (WWF), which is rich in dietary fibers, vitamins, and other bioactive compounds. The addition of WWF delayed the retrogradation tendency of starch in the dry mix. WWF-added instant noodles had softer texture, less sticky surface, and lower peroxide value. Based on the results of this study, the refined wheat flour in the recipe for instant-fried noodle could be partially replaced by WWF to make noodles with better texture profile and higher consumer acceptance. © 2017 Wiley Periodicals, Inc.

  1. Renin-angiotensin-aldosterone system inhibitors improve membrane stability and change gene-expression profiles in dystrophic skeletal muscles.

    Science.gov (United States)

    Chadwick, Jessica A; Bhattacharya, Sayak; Lowe, Jeovanna; Weisleder, Noah; Rafael-Fortney, Jill A

    2017-02-01

    Angiotensin-converting enzyme inhibitors (ACEi) and mineralocorticoid receptor (MR) antagonists are FDA-approved drugs that inhibit the renin-angiotensin-aldosterone system (RAAS) and are used to treat heart failure. Combined treatment with the ACEi lisinopril and the nonspecific MR antagonist spironolactone surprisingly improves skeletal muscle, in addition to heart function and pathology in a Duchenne muscular dystrophy (DMD) mouse model. We recently demonstrated that MR is present in all limb and respiratory muscles and functions as a steroid hormone receptor in differentiated normal human skeletal muscle fibers. The goals of the current study were to begin to define cellular and molecular mechanisms mediating the skeletal muscle efficacy of RAAS inhibitor treatment. We also compared molecular changes resulting from RAAS inhibition with those resulting from the current DMD standard-of-care glucocorticoid treatment. Direct assessment of muscle membrane integrity demonstrated improvement in dystrophic mice treated with lisinopril and spironolactone compared with untreated mice. Short-term treatments of dystrophic mice with specific and nonspecific MR antagonists combined with lisinopril led to overlapping gene-expression profiles with beneficial regulation of metabolic processes and decreased inflammatory gene expression. Glucocorticoids increased apoptotic, proteolytic, and chemokine gene expression that was not changed by RAAS inhibitors in dystrophic mice. Microarray data identified potential genes that may underlie RAAS inhibitor treatment efficacy and the side effects of glucocorticoids. Direct effects of RAAS inhibitors on membrane integrity also contribute to improved pathology of dystrophic muscles. Together, these data will inform clinical development of MR antagonists for treating skeletal muscles in DMD. Copyright © 2017 the American Physiological Society.

  2. Biomarker Profile Does Not Predict Weight Loss Success in Successful and Unsuccessful Diet-Reduced Obese Individuals: A Prospective Study

    Science.gov (United States)

    Ogden, Lorraine Garratt; MacLean, Paul Scown; Giles, Erin Danielle; Wyatt, Holly Roxanna

    2013-01-01

    Background. Individuals attempting weight reduction have varying success when participating in the same intervention. Identifying physiological factors associated with greater weight loss could improve outcomes. Methods. Sixty-one adults (BMI 27–30 kg/m2) participated in a 16-week group-based, cognitive-behavioral control weight loss program. Concentrations of 12 fasting hormones and cytokines related to adiposity, satiety/hunger, and inflammation were measured using the Milliplex human metabolic human panel before and after weight loss. Participants were grouped based on ≥8% (successful group, SG) or <8% weight loss (less successful group, LSG). Results. The SG had 46 subjects (75.4%), while the LSG had 15 (24.6%). There were no differences in baseline sex distribution, age, weight, BMI, and body composition between groups. In the SG, baseline to the 16-week levels decreased significantly for c-peptide (1,030 versus 891 pg/mL, P = 0.002), insulin (665 versus 541 pg/mL, P = 0.001), and leptin (0.83 versus 0.58 ng/mL/kg fat, P < 0.001). None of the baseline analytes predicted greater weight loss. Conclusions. Successful weight loss was associated with changes in adiposity (less fat mass) and unfavorable hunger signals. No baseline biomarker profile was associated with weight loss success. Behavioral factors may have outweighed physiological signals for determining successful weight loss. This trial is registered with Clinicaltrials.gov NCT00429650. PMID:24363955

  3. Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.

    Science.gov (United States)

    Abelin, Jennifer G; Keskin, Derin B; Sarkizova, Siranush; Hartigan, Christina R; Zhang, Wandi; Sidney, John; Stevens, Jonathan; Lane, William; Zhang, Guang Lan; Eisenhaure, Thomas M; Clauser, Karl R; Hacohen, Nir; Rooney, Michael S; Carr, Steven A; Wu, Catherine J

    2017-02-21

    Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Protein linear indices of the 'macromolecular pseudograph alpha-carbon atom adjacency matrix' in bioinformatics. Part 1: prediction of protein stability effects of a complete set of alanine substitutions in Arc repressor.

    Science.gov (United States)

    Marrero-Ponce, Yovani; Medina-Marrero, Ricardo; Castillo-Garit, Juan A; Romero-Zaldivar, Vicente; Torrens, Francisco; Castro, Eduardo A

    2005-04-15

    TOMOCOMD-CAMPS method produced a linear piecewise regression (R=0.97) between protein backbone descriptors and tm values for alanine mutants of the Arc repressor. A break-point value of 51.87 degrees C characterized two mutant clusters and coincided perfectly with the experimental scale. For this reason, we can use the linear discriminant analysis and piecewise models in combination to classify and predict the stability of the mutant Arc homodimers. These models also permitted the interpretation of the driving forces of such folding process, indicating that topologic/topographic protein backbone interactions control the stability profile of wild-type Arc and its alanine mutants.

  5. Large-eddy simulation of the atmospheric boundary layer: Influence of unsteady forcing, baroclinicity, inversion strength and stability on the wind profile

    DEFF Research Database (Denmark)

    Pedersen, Jesper Grønnegaard

    The largest wind turbines today often reach heights where traditional models of the wind speed and how it varies with height no longer can be expected to apply. For accurate assessment of wind energy resources and loads on wind turbines, there is a need for better understanding of the flow of air...... of the large-scale pressure forcing, when using LES for prediction of real-world wind profiles. In the Høvsøre case study, simulated wind speeds agree well with measurements throughout the ABL, but only when the applied forcing follows a height- and time-dependent pressure gradient estimated from continuous...... LIDAR measurements of the wind speed above the ABL. Including unsteadiness and baroclinic effects in the forcing also improves agreement with measurements in the Hamburg case study, but not as unambiguously as in the Høvsøre case study. It is concluded that the measurements available at and around...

  6. Predictive functional profiling using marker gene sequences and community diversity analyses of microbes in full-scale anaerobic sludge digesters.

    Science.gov (United States)

    Gao, Jing; Liu, Guoji; Li, Hongping; Xu, Li; Du, Lili; Yang, Bo

    2016-07-01

    Anaerobic digestion (AD) is widely used in treating the sewage sludge, as it can reduce the amount of sludge, eliminate pathogens and produce biofuel. To enhance the operational performance and stability of anaerobic bioreactors, operational and conventional chemical data from full-scale sludge anaerobic digesters were collected over a 2-year period and summarized, and the microbial community diversity of the sludge sample was investigated at various stages of the AD process. For the purpose of distinguishing between the functional and community diversity of the microbes, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software was used to impute the prevalence of 16S rDNA marker gene sequences in the difference in various sludge samples. Meanwhile, a taxa analysis was also carried out to investigate the different sludge samples. The microbial community diversity analysis of one AD sludge sample showed that the most dominant bacterial genera were Saccharicrinis, Syntrophus, Anaerotruncus and Thermanaerothrix. Among archaea, acetoclastic Methanosaeta represented 56.0 %, and hydrogenotrophic Methanospirillum, Methanoculleus, Methanothermus and Methanolinea accounted for 41.3 % of all methanogens. The taxa, genetic and functional prediction analyses of the feedstock and AD sludge samples suggested great community diversity differences between them. The taxa of bacteria in two AD sludge samples were considerably different, but the abundances of the functional KEGG pathways took on similar levels. The numbers of identified pathogens were significantly lower in the digested sludge than in the feedstock, but the PICRUSt results showed the difference in "human diseases" abundances in the level-1 pathway between the two sludge samples was small.

  7. Prevalence of classification methods for patients with lumbar impairments using the McKenzie syndromes, pain pattern, manipulation, and stabilization clinical prediction rules.

    Science.gov (United States)

    Werneke, Mark W; Hart, Dennis; Oliver, Dave; McGill, Troy; Grigsby, David; Ward, Jason; Weinberg, Jon; Oswald, William; Cutrone, Guillermo

    2010-12-01

    Aims were (1) to determine the proportion of patients with lumbar impairments who could be classified at intake by McKenzie syndromes (McK) and pain pattern classification (PPCs) using Mechanical Diagnosis and Therapy (MDT) assessment methods, manipulation, and stabilization clinical prediction rules (CPRs) and (2) for each Man CPR or Stab CPR category, determine classification prevalence rates using McK and PPC. Eight physical therapists practicing in eight diverse clinical settings classified patients typically referred to rehabilitation by McKenzie syndromes (i.e. derangement, dysfunction, posture, or other), pain pattern classification [i.e. centralization (CEN), not centralization (Non CEN), and not classified (NC)], Manipulation CPR (positive, negative), and stabilization CPR (positive, negative). Prevalence rates with 95% confidence intervals (CI) were calculated for each classification category by McK, PPC, and manipulation and stabilization CPRs. Prevalence rates (95% CIs) for McK and PPC were calculated for each CPR category separately. Data from 628 adults [mean age: 52±17 years, 56% female] were analyzed. Prevalence rates were: McK - derangement 67%, dysfunction 5%, posture 0%, other 28%; PPC - CEN 43%, Non CEN 39%, NC 18%; manipulation CPR - positive 13%; Stab CPR - positive 7%. For patients positive for manipulation CPR (n = 79), prevalence rates for derangement were 89% and CEN 68%. For patients positive for stabilization CPR (n = 41), prevalence rates for derangement were 83% and CEN 80%. The majority of patients classified based on initial clinical presentation by manipulation and stabilization CPRs were also classified as derangements whose symptoms centralized. Manipulation and stabilization CPRs may not represent a mutually exclusive treatment subgroup but may include patients who can be initially treated using a different classification method.

  8. The stability of coping strategies in older adults with osteoarthritis and the ability of these strategies to predict changes in depression, disability, and pain.

    Science.gov (United States)

    Regier, Natalie G; Parmelee, Patricia A

    2015-01-01

    Given the chronically painful, incurable nature of osteoarthritis, effective cognitive and behavioral coping strategies may be critical for older adults with the disease. Little is known about how and why coping changes over time, nor about stability of coping strategies in persons with osteoarthritis. The aims of this work were to examine the structure of coping in older adults with osteoarthritis, the association of coping strategies with well-being, the stability of coping over time, and its association with changes in well-being over the same period. In a cross-sectional study, 199 older adults with osteoarthritis of the knee were assessed at baseline and two-years' follow-up. Items from two coping scales were factor analyzed, and Pearson's correlations and paired-samples t-tests assessed relative and absolute stability of the resultant coping strategies. CFA assessed the stability of the factor structure itself. Ordinary least-squares regression analyses examined the impact of change in coping on well-being. A five-factor coping solution emerged: stoicism, refocusing, problem-solving, wishful-thinking, and emotion-focused coping. The factor structure showed stability over the two-year period. Absolute stability of strategies varied, indicating that change in coping styles was possible. Changes in coping style predicts future well-being; however, coping remains malleable with age and maladaptive strategies can be effectively targeted. Greater knowledge of the utility or maladaptive nature of a given strategy may help guide decisions about interventions for patients with osteoarthritis and encourage more adaptive coping styles.

  9. The influence of humidity fluxes on offshore wind speed profiles

    DEFF Research Database (Denmark)

    Barthelmie, Rebecca Jane; Sempreviva, Anna Maria; Pryor, Sara

    2010-01-01

    extrapolation from lower measurements. With humid conditions and low mechanical turbulence offshore, deviations from the traditional logarithmic wind speed profile become significant and stability corrections are required. This research focuses on quantifying the effect of humidity fluxes on stability corrected...... wind speed profiles. The effect on wind speed profiles is found to be important in stable conditions where including humidity fluxes forces conditions towards neutral. Our results show that excluding humidity fluxes leads to average predicted wind speeds at 150 m from 10 m which are up to 4% higher...... than if humidity fluxes are included, and the results are not very sensitive to the method selected to estimate humidity fluxes....

  10. Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity

    DEFF Research Database (Denmark)

    Rasmussen, Michael; Fenoy, Emilio; Harndahl, Mikkel

    2016-01-01

    Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally...... been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability...

  11. Stability and predictive utility, over 3 years, of the illness beliefs of individuals recently diagnosed with Type 2 diabetes mellitus

    DEFF Research Database (Denmark)

    Skinner, Timothy C.; Khunti, K.; Carey, M. E.

    2014-01-01

    Aim: To determine the stability of beliefs of patients with Type 2 diabetes about their diabetes over 3 years, following diagnosis. Methods: Data were collected as part of a multicentre cluster randomized controlled trial of a 6-h self-management programme, across 207 general practices in the UK....

  12. One-year temporal stability and predictive and incremental validity of the body, eating, and exercise comparison orientation measure (BEECOM) among college women.

    Science.gov (United States)

    Fitzsimmons-Craft, Ellen E; Bardone-Cone, Anna M

    2014-01-01

    This study examined the one-year temporal stability and the predictive and incremental validity of the Body, Eating, and Exercise Comparison Measure (BEECOM) in a sample of 237 college women who completed study measures at two time points about one year apart. One-year temporal stability was high for the BEECOM total and subscale (i.e., Body, Eating, and Exercise Comparison Orientation) scores. Additionally, the BEECOM exhibited predictive validity in that it accounted for variance in body dissatisfaction and eating disorder symptomatology one year later. These findings held even after controlling for body mass index and existing measures of social comparison orientation. However, results regarding the incremental validity of the BEECOM, or its ability to predict change in these constructs over time, were more mixed. Overall, this study demonstrated additional psychometric properties of the BEECOM among college women, further establishing the usefulness of this measure for more comprehensively assessing eating disorder-related social comparison. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Phylogeography of the genus Podococcus (Palmae/Arecaceae) in Central African rain forests: Climate stability predicts unique genetic diversity.

    Science.gov (United States)

    Faye, A; Deblauwe, V; Mariac, C; Richard, D; Sonké, B; Vigouroux, Y; Couvreur, T L P

    2016-12-01

    The tropical rain forests of Central Africa contain high levels of species diversity. Paleovegetation or biodiversity patterns suggested successive contraction/expansion phases on this rain forest cover during the last glacial maximum (LGM). Consequently, the hypothesis of the existence of refugia e.g. habitat stability that harbored populations during adverse climatic periods has been proposed. Understory species are tightly associated to forest cover and consequently are ideal markers of forest dynamics. Here, we used two central African rain forest understory species of the palm genus, Podococcus, to assess the role of past climate variation on their distribution and genetic diversity. Species distribution modeling in the present and at the LGM was used to estimate areas of climatic stability. Genetic diversity and phylogeography were estimated by sequencing near complete plastomes for over 120 individuals. Areas of climatic stability were mainly located in mountainous areas like the Monts de Cristal and Monts Doudou in Gabon, but also lowland coastal forests in southeast Cameroon and northeast Gabon. Genetic diversity analyses shows a clear North-South structure of genetic diversity within one species. This divide was estimated to have originated some 500,000years ago. We show that, in Central Africa, high and unique genetic diversity is strongly correlated with inferred areas of climatic stability since the LGM. Our results further highlight the importance of coastal lowland rain forests in Central Africa as harboring not only high species diversity but also important high levels of unique genetic diversity. In the context of strong human pressure on coastal land use and destruction, such unique diversity hotspots need to be considered in future conservation planning. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Ground-based remote sensing profiling and numerical weather prediction model to manage nuclear power plants meteorological surveillance in Switzerland

    Directory of Open Access Journals (Sweden)

    B. Calpini

    2011-08-01

    Full Text Available The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers. This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS. The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every three hours. This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plants and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release the best picture of the 24-h evolution of the air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an

  15. Differential mTOR pathway profiles in bladder cancer cell line subtypes to predict sensitivity to mTOR inhibition.

    Science.gov (United States)

    Hau, Andrew M; Nakasaki, Manando; Nakashima, Kazufumi; Krish, Goutam; Hansel, Donna E

    2017-10-01

    Molecular classification of bladder cancer has been increasingly proposed as a potential tool to predict clinical outcomes and responses to chemotherapy. Here we focused on mechanistic target of rapamycin (mTOR) inhibition as a chemotherapeutic strategy and characterized the expression profile of mTOR signaling targets in representative bladder cancer cell lines from basal, luminal, and either basal/luminal ("non-type") molecular subtypes. Protein and mRNA expression of mTOR signaling components from representative luminal (RT4 and RT112), basal (SCaBER and 5637), and nontype (T24 and J82) bladder cancer cell line subtypes were determined by Western blot and database mining analysis of the Cancer Cell Line Encyclopedia. Cell viability following treatment with either, Torin-2 or KU-0063794, 2 dual mTOR complex 1/2 inhibitors, was determined by MTT assay. Immunoblot analysis of cells treated with Torin-2 or KU-0063794 was performed to determine the effects of mTOR inhibition on expression and phosphorylation status of mTOR signaling components, Akt, 4E-BP1, and ribosomal protein S6. Molecular subtypes of bladder cancer cell lines each exhibited a distinct pattern of expression of mTOR-associated genes and baseline phosphorylation level of Akt and 4E-BP1. Cells with low levels of Akt Ser-473 phosphorylation were more resistant to the cytotoxic effects of mTOR inhibition with Torin-2, but not KU-0063794. Exposure to Torin-2 and KU-0063794 both potently and rapidly inhibited phosphorylation of Akt Ser-473 and Thr-308, and 4E-BP1 T37/46 in cell lines that included basal and nontype subtypes. Differential gene expression and protein activity associated with mTOR signaling is observed among bladder cancer cell lines stratified into basal, luminal, and nontype subtypes. Urothelial carcinomas characterized by high baseline Akt Ser-473 phosphorylation may be best suited for targeted mTOR therapies. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Computationally-predicted CB1 cannabinoid receptor mutants show distinct patterns of salt-bridges that correlate with their level of constitutive activity reflected in G protein coupling levels, thermal stability, and ligand binding.

    Science.gov (United States)

    Ahn, Kwang H; Scott, Caitlin E; Abrol, Ravinder; Goddard, William A; Kendall, Debra A

    2013-08-01

    The cannabinoid receptor 1 (CB1), a member of the class A G-protein-coupled receptor (GPCR) family, possesses an observable level of constitutive activity. Its activation mechanism, however, has yet to be elucidated. Previously we discovered dramatic changes in CB1 activity due to single mutations; T3.46A, which made the receptor inactive, and T3.46I and L3.43A, which made it essentially fully constitutively active. Our subsequent prediction of the structures of these mutant receptors indicated that these changes in activity are explained in terms of the pattern of salt-bridges in the receptor region involving transmembrane domains 2, 3, 5, and 6. Here we identified key salt-bridges, R2.37 + D6.30 and D2.63 + K3.28, critical for CB1 inactive and active states, respectively, and generated new mutant receptors that we predicted would change CB1 activity by either precluding or promoting these interactions. We find that breaking the R2.37 + D6.30 salt-bridge resulted in substantial increase in G-protein coupling activity and reduced thermal stability relative to the wild-type reflecting the changes in constitutive activity from inactive to active. In contrast, breaking the D2.63 + K3.28 salt-bridge produced the opposite profile suggesting this interaction is critical for the receptor activation. Thus, we demonstrate an excellent correlation with the predicted pattern of key salt-bridges and experimental levels of activity and conformational flexibility. These results are also consistent with the extended ternary complex model with respect to shifts in agonist and inverse agonist affinity and provide a powerful framework for understanding the molecular basis for the multiple stages of CB1 activation and that of other GPCRs in general. Copyright © 2013 Wiley Periodicals, Inc., a Wiley company.

  17. Evaluation of feasible machine learning techniques for predicting the time to fly and aircraft speed profile on final approach : Predictive dynamic support tool on final approach

    NARCIS (Netherlands)

    Herrema, F.F.; Treve, V; Curran, R.; Visser, H.G.; Lovell, D.; Fricke, H.

    2016-01-01

    currently, at many airports, the runway throughput is the limiting factor for the overall capacity. Among the most important constraining parameters is the separation minima expressed in distance. On the top of these minima, the difference of the leader and follower aircraft speed profiles imposes

  18. Predicting the dental implant stability based on the antiresonance phase of a piezo-based impedance sensor

    Directory of Open Access Journals (Sweden)

    Paramita Banerjee

    2017-01-01

    Full Text Available Background: The stability of dental implants (DIs in in vivo tests can be determined using noninvasive resonance frequency analysis technique. A low-cost piezo-based sensor has been developed for this purpose which uses a readily available two-terminal piezo element, to which a metal substrate is adhesively glued for attaching the implant. Aim: The attainment of implant stability in dynamic tests using this sensor must be standardized in terms of the major antiresonance (AR in the impedance phase responses using sensor-DI assembly. This will be used to predetermine the dimensions of the glued metal substrate in the sensor design. Materials and Methods: Multiple sensors with varying sensor dimensions were developed. Static and dynamic impedance studies were performed on these and corresponding sensor-implant assemblies. Static tests as well as in vitro tests with the sensor-implant assembly dipped in a standardized dental plaster mixture were performed in controlled laboratory conditions. Results: The probability of acceptance of the hypothesis has been checked using binomial distribution with a significance level of 5%. Statistically observed that for 95% of the cases where the DI becomes stable in dental plaster, both AR phase and AR frequency (ARF return to their corresponding static values. Furthermore, for a piezo element, whose ARF is within 6–6.6 kHz, the sensor yields maximal phase when the length of the metallic strip is 2 cm. Conclusions: Experimental validation supports both claims. Hence, this work can be extended to in vivo DI stability determination and design aspects of the corresponding sensor.

  19. Predictive Parameters of Oral Health Quality of Life in Complete Mandibular Denture Wearers Stabilized by Mini-Implants: A Two-Year Follow-Up Study

    Directory of Open Access Journals (Sweden)

    Cindy Batisse

    2017-10-01

    Full Text Available The frequent instability of mandibular removable complete dentures affects patient Oral Health Related Quality of Life (OHRQoL. An innovative therapeutic strategy used to improve stability involves placing four symphyseal mini-implants. This study was aimed at assessing OHRQoL over time in subjects in which mini-implants were placed and exploring if certain parameters could predict the evolution of their OHRQoL. The OHRQoL of subjects with dentures was assessed using the Geriatric Oral Health Assessment Index (GOHAI before (T0, 2–6 months (T1, twelve months (T2 and twenty-four or more months (T3 after mini-implant setting. Age, gender and chewing ability were tested as explanatory variables for the change in OHRQoL with time. Thirteen women and six men were included (mean age: 69 ± 10 years. After treatment, mean GOHAI scores at T1, T2 and T3 increased significantly (p < 0.001. The GOHAI-Add mean score was not affected by age or gender. Baseline chewing ability impacted the “functional” and “pain and discomfort” fields of the mean GOHAI scores (p < 0.05. The OHRQoL quickly improved after mini-implant placement in complete denture wearers and then stabilized over time. Baseline chewing ability can be used as a predictive parameter of OHRQoL.

  20. Sensory Bias Predicts Postural Stability, Anxiety, and Cognitive Performance in Healthy Adults Walking in Novel Discordant Conditions

    Science.gov (United States)

    Brady, Rachel A.; Batson, Crystal D.; Peters, Brian T.; Mulavara, Ajitkumar P.; Bloomberg, Jacob J.

    2010-01-01

    We designed a gait training study that presented combinations of visual flow and support surface manipulations to investigate the response of healthy adults to novel discordant sensorimotor conditions. We aimed to determine whether a relationship existed between subjects visual dependence and their scores on a collective measure of anxiety, cognition, and postural stability in a new discordant environment presented at the conclusion of training (Transfer Test). A treadmill was mounted to a motion base platform positioned 2 m behind a large visual screen. Training consisted of three walking sessions, each within a week of the previous visit, that presented four 5-minute exposures to various combinations of support surface and visual scene manipulations, all lateral sinusoids. The conditions were scene translation only, support surface translation only, simultaneous scene and support surface translations in-phase, and simultaneous scene and support surface translations 180 out-of-phase. During the Transfer Test, the trained participants received a 2-minute novel exposure. A visual sinusoidal roll perturbation, with twice the original flow rate, was superimposed on a sinusoidal support surface roll perturbation that was 90 out of phase with the scene. A high correlation existed between normalized torso translation, measured in the scene-only condition at the first visit, and a combined measure of normalized heart rate, stride frequency, and reaction time at the transfer test. Results suggest that visually dependent participants experience decreased postural stability, increased anxiety, and increased reaction times compared to their less visually dependent counterparts when negotiating novel discordant conditions.

  1. A predictive numerical model for potential mapping of the gas hydrate stability zone in the Gulf of Cadiz

    Science.gov (United States)

    Leon, R.; Somoza, L.

    2009-04-01

    This comunication presents a computational model for mapping the regional 3D distribution in which seafloor gas hydrates would be stable, that is carried out in a Geographical Information System (GIS) environment. The construction of the model is comprised of three primary steps, namely (1) the construction of surfaces for the various variables based on available 3D data (seafloor temperature, geothermal gradient and depth-pressure); (2) the calculation of the gas function equilibrium functions for the various hydrocarbon compositions reported from hydrate and sediment samples; and (3) the calculation of the thickness of the hydrate stability zone. The solution is based on a transcendental function, which is solved iteratively in a GIS environment. The model has been applied in the northernmost continental slope of the Gulf of Cadiz, an area where an abundant supply for hydrate formation, such as extensive hydrocarbon seeps, diapirs and fault structures, is combined with deep undercurrents and a complex seafloor morphology. In the Gulf of Cadiz, model depicts the distribution of the base of the gas hydrate stability zone for both biogenic and thermogenic gas compositions, and explains the geometry and distribution of geological structures derived from gas venting in the Tasyo Field (Gulf of Cadiz) and the generation of BSR levels on the upper continental slope.

  2. Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the remediation of arsenite from water using the response surface methodology (RSM) model: Modeling and optimization.

    Science.gov (United States)

    Mohammadi, Amir; Nemati, Sepideh; Mosaferi, Mohammad; Abdollahnejhad, Ali; Almasian, Mohammad; Sheikhmohammadi, Amir

    2017-08-01

    This study aimed to investigate the feasibility of carboxymethyl cellulose-stabilized iron nanoparticles (C-nZVI) for the removal of arsenite ions from aqueous solutions. Iron nanoparticles and carboxymethyl cellulose-stabilized iron nanoparticles were freshly synthesized. The synthesized nanomaterials had a size of 10nm approximately. The transmission electron microscope (TEM) images depicted bulkier dendrite flocs of non-stabilized iron nanoparticles. It described nanoscale particles as not discrete resulting from the aggregation of particles. The scanning electron microscopy (SEM) image showed that C-nZVI is approximately discrete, well-dispersed and an almost spherical shape. The energy dispersive x-ray spectroscopy (EDAX) and X-ray diffraction (XRD) spectrum confirmed the presence of Fe(0) in the C-nZVI composite. The central composite design under the Response Surface Methodology (RSM) was employed in order to investigate the effect of independent variables on arsenite removal and to determine the optimum condition. The reduced full second-order model indicated a well-fitted model since the experimental values were in good agreement with it. Therefore, this model is used for the prediction and optimization of arsenite removal from water. The maximum removal efficiency was estimated to be 100% when all parameters are considered simultaneously. The predicted optimal conditions for the maximum removal efficiency were achieved with initial arsenite concentration, 0.68mgL(-1); C-nZVI, 0.3 (gL(-1)); time, 31.25 (min) and pH, 5.2. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Link between structural and mechanical stability of fcc- and bcc-based ordered MgeLi alloys

    CSIR Research Space (South Africa)

    Phasha, MJ

    2010-06-01

    Full Text Available properties of cubic-based MgeLi alloys. The heats of formation and elastic moduli were used in predicting structural stability profile, and their results are consistent with each other. In terms of phase stability, an interesting correlation between...

  4. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  5. 'Omics' for microbial food stability: Proteomics for the development of predictive models for bacterial spore stress survival and outgrowth.

    Science.gov (United States)

    Abhyankar, Wishwas; Stelder, Sacha; de Koning, Leo; de Koster, Chris; Brul, Stanley

    2017-01-02

    Bacterial spores are ubiquitous in nature. They are stress resistant entities that are a concern to microbiological food stability due to their environmental stress resistance. In addition germinating and outgrowing spores at undesired times and places pose a significant health burden. The challenge is amplified due to the heterogeneous germination and outgrowth behaviour of isogenic spore populations. We discuss the role of different 'omics' techniques, proteomics in particular, to study spore biology in detail. With examples, the use of label-based and label-free quantitative proteomics approaches in understanding the spore physiology is demonstrated. Also the need of genomics, single cell analyses and analysis of cellular physiology is discussed briefly. Certainly accurate comprehensive data obtained from omics methods and molecular physiology will underpin the development of robust molecular models of bacterial spore germination and outgrowth. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model.

    Science.gov (United States)

    Baars, Erik W; van der Hart, Onno; Nijenhuis, Ellert R S; Chu, James A; Glas, Gerrit; Draijer, Nel

    2011-01-01

    The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID). We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex PTSD therapists), and in the second round we surveyed a subset of 22 of the 42 therapists (13 DID and 9 complex PTSD therapists). First, we drew on therapists' knowledge of prognostic factors for stabilization-oriented treatment of complex PTSD and DID. Second, therapists prioritized a list of prognostic factors by estimating the size of each variable's prognostic effect; we clustered these factors according to content and named the clusters. Next, concept mapping methodology and statistical analyses (including principal components analyses) were used to transform individual judgments into weighted group judgments for clusters of items. A prognostic model, based on consensually determined estimates of effect sizes, of 8 clusters containing 51 factors for both complex PTSD and DID was formed. It includes the clusters lack of motivation, lack of healthy relationships, lack of healthy therapeutic relationships, lack of other internal and external resources, serious Axis I comorbidity, serious Axis II comorbidity, poor attachment, and self-destruction. In addition, a set of 5 DID-specific items was constructed. The model is supportive of the current phase-oriented treatment model, emphasizing the strengthening of the therapeutic relationship and the patient's resources in the initial stabilization phase. Further research is needed to test the model's statistical and clinical validity.

  7. Distinguishing predictive profiles for patient-based risk assessment and diagnostics of plaque induced, surgically and prosthetically triggered peri-implantitis.

    Science.gov (United States)

    Canullo, Luigi; Tallarico, Marco; Radovanovic, Sandro; Delibasic, Boris; Covani, Ugo; Rakic, Mia

    2016-10-01

    To investigate whether specific predictive profiles for patient-based risk assessment/diagnostics can be applied in different subtypes of peri-implantitis. This study included patients with at least two implants (one or more presenting signs of peri-implantitis). Anamnestic, clinical, and implant-related parameters were collected and scored into a single database. Dental implant was chosen as the unit of analysis, and a complete screening protocol was established. The implants affected by peri-implantitis were then clustered into three subtypes in relation to the identified triggering factor: purely plaque-induced or prosthetically or surgically triggered peri-implantitis. Statistical analyses were performed to compare the characteristics and risk factors between peri-implantitis and healthy implants, as well as to compare clinical parameters and distribution of risk factors between plaque, prosthetically and surgically triggered peri-implantitis. The predictive profiles for subtypes of peri-implantitis were estimated using data mining tools including regression methods and C4.5 decision trees. A total of 926 patients previously treated with 2812 dental implants were screened for eligibility. Fifty-six patients (6.04%) with 332 implants (4.44%) met the study criteria. Data from 125 peri-implantitis and 207 healthy implants were therefore analyzed and included in the statistical analysis. Within peri-implantitis group, 51 were classified as surgically triggered (40.8%), 38 as prosthetically triggered (30.4%), and 36 as plaque-induced (28.8%) peri-implantitis. For peri-implantitis, 51 were associated with surgical risk factor (40.8%), 38 with prosthetic risk factor (30.4%), 36 with purely plaque-induced risk factor (28.8%). The variables identified as predictors of peri-implantitis were female sex (OR = 1.60), malpositioning (OR = 48.2), overloading (OR = 18.70), and bone reconstruction (OR = 2.35). The predictive model showed 82.35% of accuracy and

  8. The affective profiles, psychological well-being, and harmony: environmental mastery and self-acceptance predict the sense of a harmonious life

    Science.gov (United States)

    Al Nima, Ali; Kjell, Oscar N.E.

    2014-01-01

    the dimensions of psychological well-being within the four affective profiles. Specifically, harmony in life was significantly predicted by environmental mastery and self-acceptance across all affective profiles. However, for the low affective group high purpose in life predicted low levels of harmony in life. Conclusions. The results demonstrated that affective profiles systematically relate to psychological well-being and harmony in life. Notably, individuals categorised as self-fulfilling tended to report higher levels of both psychological well-being and harmony in life when compared with the other profiles. Meanwhile individuals in the self-destructive group reported the lowest levels of psychological well-being and harmony when compared with the three other profiles. It is proposed that self-acceptance and environmental acceptance might enable individuals to go from self-destructive to a self-fulfilling state that also involves harmony in life. PMID:24688843

  9. Evaluation of models to predict the stoichiometry of volatile fatty acid profiles in rumen fluid of lactating Holstein cows

    NARCIS (Netherlands)

    Morvay, Y.; Bannink, A.; France, J.; Kebreab, E.; Dijkstra, J.

    2011-01-01

    Volatile fatty acids (VFA), produced in the rumen by microbial fermentation, are the main energy source for ruminants. The VFA profile, particularly the nonglucogenic (acetate, Ac; butyrate, Bu) to glucogenic (propionate, Pr) VFA ratio (NGR), is associated with effects on methane production, milk

  10. Profiling cancer

    DEFF Research Database (Denmark)

    Ciro, Marco; Bracken, Adrian P; Helin, Kristian

    2003-01-01

    In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

  11. Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.

    Science.gov (United States)

    Bartsch, Georg; Mitra, Anirban P; Mitra, Sheetal A; Almal, Arpit A; Steven, Kenneth E; Skinner, Donald G; Fry, David W; Lenehan, Peter F; Worzel, William P; Cote, Richard J

    2016-02-01

    Due to the high recurrence risk of nonmuscle invasive urothelial carcinoma it is crucial to distinguish patients at high risk from those with indolent disease. In this study we used a machine learning algorithm to identify the genes in patients with nonmuscle invasive urothelial carcinoma at initial presentation that were most predictive of recurrence. We used the genes in a molecular signature to predict recurrence risk within 5 years after transurethral resection of bladder tumor. Whole genome profiling was performed on 112 frozen nonmuscle invasive urothelial carcinoma specimens obtained at first presentation on Human WG-6 BeadChips (Illumina®). A genetic programming algorithm was applied to evolve classifier mathematical models for outcome prediction. Cross-validation based resampling and gene use frequencies were used to identify the most prognostic genes, which were combined into rules used in a voting algorithm to predict the sample target class. Key genes were validated by quantitative polymerase chain reaction. The classifier set included 21 genes that predicted recurrence. Quantitative polymerase chain reaction was done for these genes in a subset of 100 patients. A 5-gene combined rule incorporating a voting algorithm yielded 77% sensitivity and 85% specificity to predict recurrence in the training set, and 69% and 62%, respectively, in the test set. A singular 3-gene rule was constructed that predicted recurrence with 80% sensitivity and 90% specificity in the training set, and 71% and 67%, respectively, in the test set. Using primary nonmuscle invasive urothelial carcinoma from initial occurrences genetic programming identified transcripts in reproducible fashion, which were predictive of recurrence. These findings could potentially impact nonmuscle invasive urothelial carcinoma management. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  12. An analytical model for the prediction of the dynamic response of premixed flames stabilized on a heat-conducting perforated plate

    KAUST Repository

    Kedia, Kushal S.

    2013-01-01

    The dynamic response of a premixed flame stabilized on a heat-conducting perforated plate depends critically on their coupled thermal interaction. The objective of this paper is to develop an analytical model to capture this coupling. The model predicts the mean flame base standoff distance; the flame base area, curvature and speed; and the burner plate temperature given the operating conditions; the mean velocity, temperature and equivalence ratio of the reactants; thermal conductivity and the perforation ratio of the burner. This coupled model is combined with our flame transfer function (FTF) model to predict the dynamic response of the flame to velocity perturbations. We show that modeling the thermal coupling between the flame and the burner, while accounting for the two-dimensionality of the former, is critical to predicting the dynamic response characteristics such as the overshoot in the gain curve (resonant condition) and the phase delay. Good agreement with the numerical and experimental results is demonstrated over a range of conditions. © 2012 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

  13. The Predictive Effects of Early Pregnancy Lipid Profiles and Fasting Glucose on the Risk of Gestational Diabetes Mellitus Stratified by Body Mass Index

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available This study aimed at evaluating the predictive effects of early pregnancy lipid profiles and fasting glucose on the risk of gestational diabetes mellitus (GDM in patients stratified by prepregnancy body mass index (p-BMI and to determine the optimal cut-off values of each indicator for different p-BMI ranges. A retrospective system cluster sampling survey was conducted in Beijing during 2013 and a total of 5,265 singleton pregnancies without prepregnancy diabetes were included. The information for each participant was collected individually using questionnaires and medical records. Logistic regression analysis and receiver operator characteristics analysis were used in the analysis. Outcomes showed that potential markers for the prediction of GDM include early pregnancy lipid profiles (cholesterol, triacylglycerols, low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratios [LDL-C/HDL-C], and triglyceride to high-density lipoprotein cholesterol ratios [TG/HDL-C] and fasting glucose, of which fasting glucose level was the most accurate indicator. Furthermore, the predictive effects and cut-off values for these factors varied according to p-BMI. Thus, p-BMI should be a consideration for the risk assessment of pregnant patients for GDM development.

  14. Non-invasive metabolomic profiling of embryo culture media and morphology grading to predict implantation outcome in frozen-thawed embryo transfer cycles.

    Science.gov (United States)

    Li, Xiong; Xu, Yan; Fu, Jing; Zhang, Wen-Bi; Liu, Su-Ying; Sun, Xiao-Xi

    2015-11-01

    Assessment of embryo viability is a crucial component of in vitro fertilization and currently relies largely on embryo morphology and cleavage rate. Because morphological assessment remains highly subjective, it can be unreliable in predicting embryo viability. This study investigated the metabolomic profiling of embryo culture media using near-infrared (NIR) spectroscopy for predicting the implantation potential of human embryos in frozen-thawed embryo transfer (FET) cycles. Spent embryo culture media was collected on day 4 after thawed embryo transfer (n = 621) and analysed using NIR spectroscopy. Viability scores were calculated using a predictive multivariate algorithm of fresh embryos with known pregnancy outcomes. The mean viability indices of embryos resulting in clinical pregnancy following FET were significantly higher than those of non-implanted embryos and differed between the 0, 50, and 100 % implantation groups. Notably, the 0 % group index was significantly lower than the 100 % implantation group index (-0.787 ± 0.382 vs. 1.064 ± 0.331, P  0.05). NIR metabolomic profiling of thawed embryo culture media is independent of morphology and correlates with embryo implantation potential in FET cycles. The viability score alone or in conjunction with morphologic grading is a more objective marker for implantation outcome in FET cycles than morphology alone.

  15. Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods To Predict Usage, Age, and Harvest Season.

    Science.gov (United States)

    Anastasiadi, Maria; Mohareb, Fady; Redfern, Sally P; Berry, Mark; Simmonds, Monique S J; Terry, Leon A

    2017-07-05

    The present study represents the first major attempt to characterize the biochemical profile in different tissues of a large selection of apple cultivars sourced from the United Kingdom's National Fruit Collection comprising dessert, ornamental, cider, and culinary apples. Furthermore, advanced machine learning methods were applied with the objective to identify whether the phenolic and sugar composition of an apple cultivar could be used as a biomarker fingerprint to differentiate between heritage and mainstream commercial cultivars as well as govern the separation among primary usage groups and harvest season. A prediction accuracy of >90% was achieved with the random forest method for all three models. The results highlighted the extraordinary phytochemical potency and unique profile of some heritage, cider, and ornamental apple cultivars, especially in comparison to more mainstream apple cultivars. Therefore, these findings could guide future cultivar selection on the basis of health-promoting phytochemical content.

  16. Theoretical Prediction of Surface Stability and Morphology of LiNiO2Cathode for Li Ion Batteries.

    Science.gov (United States)

    Cho, Eunseog; Seo, Seung-Woo; Min, Kyoungmin

    2017-09-27

    Ni-rich layered oxides are considered to be a promising cathode material with high capacity, and their surface structure should be extensively explored to understand the complex associated phenomena. We investigated the surface stability and morphology of LiNiO 2 as a representative of these materials by using density functional theory calculations. The results reveal that the Li-exposed surfaces have lower energies than the oxygen surfaces, irrespective of the facets, and the Ni-exposed ones are the least stable. The equilibrium morphology can vary from truncated trigonal bipyramid to truncated egg shape, according to the chemical potential, whose range is confined by the phase diagram. Moreover, the electrochemical window of stable facets is found to strongly depend on the surface elements rather than the facet directions. Contrary to the stable Li surfaces, oxygen exposure on the surface considerably lowers the Fermi level to the level of electrolyte, thereby accelerating oxidative decomposition of the electrolyte on the cathode surface.

  17. Predicting sickness impact profile at six months after stroke: further results from the European multi-center CERISE study

    NARCIS (Netherlands)

    Stummer, C.A.; Verheyden, G.; Putman, K.; Jenni, W.; Schupp, W.; Wit, L. De

    2015-01-01

    PURPOSE: To develop prognostic models and equations for predicting participation at six months after stroke. METHODS: This European prospective cohort study recruited 532 consecutive patients from four rehabilitation centers. Participation was assessed at six months after stroke with the Sickness

  18. Development of a Multivariate Predictive Model to Estimate Ionized Calcium Concentration from Serum Biochemical Profile Results in Dogs

    OpenAIRE

    Danner, J.; Ridgway, M.D.; Rubin, S I; Le Boedec, K.

    2017-01-01

    Background Ionized calcium concentration is the gold standard to assess calcium status in dogs, but measurement is not always available. Objectives (1) To predict ionized calcium concentration from biochemical results and compare the diagnostic performance of predicted ionized calcium concentration (piCa) to those of total calcium concentration (tCa) and 2 corrected tCa formulas; and (2) to study the relationship between biochemical results and variation of measured ionized calcium concentrat...

  19. Bio-Soliton Model that predicts Non-Thermal Electromagnetic Radiation Frequency Bands, that either Stabilize or Destabilize Life Conditions

    CERN Document Server

    Geesink, J H

    2016-01-01

    Solitons, as self-reinforcing solitary waves, interact with complex biological phenomena such as cellular self-organisation. Soliton models are able to describe a spectrum of electromagnetism modalities that can be applied to understand the physical principles of biological effects in living cells, as caused by electromagnetic radiation. A bio-soliton model is proposed, that enables to predict which eigen-frequencies of non-thermal electromagnetic waves are life-sustaining and which are, in contrast, detrimental for living cells. The particular effects are exerted by a range of electromagnetic wave frequencies of one-tenth of a Hertz till Peta Hertz, that show a pattern of twelve bands, if positioned on an acoustic frequency scale. The model was substantiated by a meta-analysis of 240 published papers of biological radiation experiments, in which a spectrum of non-thermal electromagnetic waves were exposed to living cells and intact organisms. These data support the concept of coherent quantized electromagnet...

  20. Molecular profiles as predictive marker for the effect of overall treatment time of radiotherapy in supraglottic larynx squamous cell carcinomas

    DEFF Research Database (Denmark)

    Eriksen, Jesper Grau; Buffa, F.M.; Alsner, Jan

    2004-01-01

    BACKGROUND AND PURPOSE: Reduction of the overall treatment time of radiotherapy increases the probability of local tumour control, but it does not benefit all patients. Identification of molecular marker profiles may aid in the selection of patients likely to benefit from accelerated radiotherapy....... PATIENTS AND METHODS: Two hundred and nine patients with SCC of the supraglottic larynx received primary radiotherapy in the randomised DAHANCA trials to 66-68 Gy, 2 Gy/fx but with different overall treatment times of 9.5 week, 6.5 week and 5.5 week. Formalin-fixed paraffin embedded tumour slides were...... as the endpoint. CONCLUSIONS: Molecular marker profiling may aid in the selection of patients that will benefit of a reduction in overall treatment time of radiotherapy in SCC of the supraglottic larynx....

  1. Prediction of the stability of BWR reactors during the start-up process; Prediccion de la estabilidad de reactores BWR durante el proceso de arranque

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz E, J.A.; Castillo D, R. [ININ, Km. 36.5 Carretera Mexico-Toluca, 52045 Salazar, Estado de Mexico (Mexico); Blazquez M, J.B. [Centro de Investigaciones Energetics, Medioambientales y Tecnologicas, Av Complutense 22, 28040 Madrid (Spain)

    2004-07-01

    The Boiling Water Reactors (BWR) are susceptible of uncertainties of power when they are operated to low flows of coolant (W) and high powers (P), being presented this situation mainly in the start-up process. The start-up process could be made but sure if the operator knew the value of the stability index Decay reason (Dr) before going up power and therefore to guarantee the stability. The power and the flow are constantly measures, the index Dr could also be considered its value in real time. The index Dr depends on the power, flow and many other values, such as, the distribution of the flow axial and radial neutronic, the temperature of the feeding water, the fraction of holes and other thermohydraulic and nuclear parameters. A simple relationship of Dr is derived leaving of the pattern reduced of March-Leuba, where three independent variables are had that are the power, the flow and a parameter that it contains the rest of the phenomenology, that is to say all the other quantities that affect the value of Dr. This relationship developed work presently and verified its prediction with data of start-up of commercial reactors could be used for the design of a practical procedure practice of start-up, what would support to the operator to prevent this type of events of uncertainty. (Author)

  2. Surface energy effects on the stability of anatase and rutile nanocrystals: A predictive diagram for Nb2O5-doped-TiO2

    Science.gov (United States)

    da Silva, Andre Luiz; Hotza, Dachamir; Castro, Ricardo H. R.

    2017-01-01

    Titanium dioxide nanoparticles are widely used for photocatalysis, and the relative fraction of titanium dioxide polymorph, i.e. anatase, rutile, or brookite, significantly affects the final performance. Even though conventional phase diagrams indicate a higher stability for the rutile polymorph, it is well established that nanosizes benefit the anatase phase due to its smaller surface energy. However, doping elements are expected to change this behavior, once changes in both surface and bulk energies may occur. Nb2O5 is commonly added to TiO2 to allow property control. However, the effect of niobium on the relative stability of anatase and rutile phases is not well understood from the thermodynamic point of view. The objective of this work was to build a new predictive nanoscale phase diagram for Nb2O5-doped TiO2. Water adsorption microcalorimetry and high temperature oxide melt solution were used to obtain the surface and bulk enthalpies. The phase diagram obtained shows the stable titania polymorph as a function of the composition and size.

  3. Predicting the liquefaction phenomena from shear velocity profiling: Empirical approach to 6.3 Mw, May 2006 Yogyakarta earthquake

    Science.gov (United States)

    Hartantyo, Eddy; Brotopuspito, Kirbani S.; Sismanto, Waluyo

    2015-04-01

    The liquefactions phenomena have been reported after a shocking 6.5Mw earthquake hit Yogyakarta province in the morning at 27 May 2006. Several researchers have reported the damage, casualties, and soil failure due to the quake, including the mapping and analyzing the liquefaction phenomena. Most of them based on SPT test. The study try to draw the liquefaction susceptibility by means the shear velocity profiling using modified Multichannel Analysis of Surface Waves (MASW). This paper is a preliminary report by using only several measured MASW points. The study built 8-channel seismic data logger with 4.5 Hz geophones for this purpose. Several different offsets used to record the high and low frequencies of surface waves. The phase-velocity diagrams were stacked in the frequency domain rather than in time domain, for a clearer and easier dispersion curve picking. All codes are implementing in Matlab. From these procedures, shear velocity profiling was collected beneath each geophone's spread. By mapping the minimum depth of shallow water table, calculating PGA with soil classification, using empirical formula for saturated soil weight from shear velocity profile, and calculating CRR and CSR at every depth, the liquefaction characteristic can be identify in every layer. From several acquired data, a liquefiable potential at some depth below water table was obtained.

  4. Predicting the liquefaction phenomena from shear velocity profiling: Empirical approach to 6.3 Mw, May 2006 Yogyakarta earthquake

    Energy Technology Data Exchange (ETDEWEB)

    Hartantyo, Eddy, E-mail: hartantyo@ugm.ac.id [PhD student, Physics Department, FMIPA, UGM. Sekip Utara Yogyakarta 55281 Indonesia (Indonesia); Brotopuspito, Kirbani S.; Sismanto; Waluyo [Geophysics Laboratory, FMIPA, Universitas Gadjah Mada, Sekip Utara Yogyakarta 55281 (Indonesia)

    2015-04-24

    The liquefactions phenomena have been reported after a shocking 6.5Mw earthquake hit Yogyakarta province in the morning at 27 May 2006. Several researchers have reported the damage, casualties, and soil failure due to the quake, including the mapping and analyzing the liquefaction phenomena. Most of them based on SPT test. The study try to draw the liquefaction susceptibility by means the shear velocity profiling using modified Multichannel Analysis of Surface Waves (MASW). This paper is a preliminary report by using only several measured MASW points. The study built 8-channel seismic data logger with 4.5 Hz geophones for this purpose. Several different offsets used to record the high and low frequencies of surface waves. The phase-velocity diagrams were stacked in the frequency domain rather than in time domain, for a clearer and easier dispersion curve picking. All codes are implementing in Matlab. From these procedures, shear velocity profiling was collected beneath each geophone’s spread. By mapping the minimum depth of shallow water table, calculating PGA with soil classification, using empirical formula for saturated soil weight from shear velocity profile, and calculating CRR and CSR at every depth, the liquefaction characteristic can be identify in every layer. From several acquired data, a liquefiable potential at some depth below water table was obtained.

  5. Long-Term Stability of Membership in a Wechsler Intelligence Scale for Children--Third Edition (WISC-III) Subtest Core Profile Taxonomy

    Science.gov (United States)

    Borsuk, Ellen R.; Watkins, Marley W.; Canivez, Gary L.

    2006-01-01

    Although often applied in practice, clinically based cognitive subtest profile analysis has failed to achieve empirical support. Nonlinear multivariate subtest profile analysis may have benefits over clinically based techniques, but the psychometric properties of these methods must be studied prior to their implementation and interpretation. The…

  6. Prediction of stabilities, mechanical properties and electronic structures of tetragonal 3d transition metal disilicides: A first-principles investigation

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Xiaohong, E-mail: zhangxiaohong@hrbeu.edu.cn [College of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150001 (China); Wang Zhengping, E-mail: zpwang@hrbeu.edu.cn [College of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150001 (China); College of Science, Harbin Engineering University, Harbin 150001 (China); Qiao Yingjie [College of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150001 (China)

    2011-08-15

    The phase stabilities, mechanical properties and electronic structures of 3d transition metal disilicides were systematically investigated by first-principles calculations. The results indicated that the crystal volume and melting temperature of the compounds increase at first and then drop again with the filling of electrons on the bonding and anti-bonding states. For tetragonal TiSi{sub 2}, NiSi{sub 2}, CuSi{sub 2} and ZnSi{sub 2}, the calculated formation energies and elastic constants confirmed that they are either thermodynamically unstable or mechanically unstable. According to the electronic structures, it can be identified that almost all the Si-Si (I) and Si-TM (I) bonds (type I) are stronger than the Si-TM (II) and Si-TM (II) (type II) ones. Therefore, the elastic deformation resistance along the <0 0 1> direction for the compounds are expected to be larger than those along the <1 0 0> and <0 1 0> directions, demonstrated by the calculated C{sub 11}, C{sub 33}, E{sub x} (E{sub y}) and E{sub z} values. Despite of the elastic constants and moduli, the results also showed that the Si-Si (I) and Si-TM (I) bonds are very important for elucidating the interfacial behaviors of the {l_brace}0 0 1{r_brace} crystal plane. For tetragonal VSi{sub 2} and CrSi{sub 2}, the Si-Si (I) bonds are half the size of the Si-TM (I) ones, leading to a preferential cleavage of the Si-TM interface, and therefore they show brittle characteristics. However, the situations in FeSi{sub 2} and CoSi{sub 2} are different. The moderate bonding strength of type I bonds and the uniform distributions of electron density on different {l_brace}0 0 1{r_brace} interfaces indicate that slip systems preferentially appear. Therefore, FeSi{sub 2} and CoSi{sub 2} possess excellent ductility.

  7. Stabilization of Resveratrol in Blood Circulation by Conjugation to mPEG and mPEG-PLA Polymers: Investigation of Conjugate Linker and Polymer Composition on Stability, Metabolism, Antioxidant Activity and Pharmacokinetic Profile: e0118824

    National Research Council Canada - National Science Library

    Basavaraj Siddalingappa; Heather A E Benson; David H Brown; Kevin T Batty; Yan Chen

    2015-01-01

    .... But undergoes rapid metabolism in the body (half life 0.13h). Hence Polymer conjugation utilizing different chemical linkers and polymer compositions was investigated for enhanced pharmacokinetic profile of resveratrol...

  8. Stabilization of resveratrol in blood circulation by conjugation to mPEG and mPEG-PLA polymers: investigation of conjugate linker and polymer composition on stability, metabolism, antioxidant activity and pharmacokinetic profile

    National Research Council Canada - National Science Library

    Siddalingappa, Basavaraj; Benson, Heather A E; Brown, David H; Batty, Kevin T; Chen, Yan

    2015-01-01

    .... But undergoes rapid metabolism in the body (half life 0.13h). Hence Polymer conjugation utilizing different chemical linkers and polymer compositions was investigated for enhanced pharmacokinetic profile of resveratrol...

  9. Prediction of the waste stabilization pond performance using linear multiple regression and multi-layer perceptron neural network: a case study of Birjand, Iran

    Directory of Open Access Journals (Sweden)

    Maryam Khodadadi

    2016-06-01

    Full Text Available Background: Data mining (DM is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (WSP in Birjand, a city in Eastern Iran. Methods: Multiple regression (MR and neural network (NN models were examined using influent characteristics (pH, Biochemical oxygen demand [BOD5], temperature, chemical oxygen demand [COD], total suspended solids [TSS], total dissolved solid [TDS], electrical conductivity [EC] and turbidity as the regression input vectors. Models were adjusted to input attributes, effluent BOD5 (BODout and COD (CODout. The models performances were estimated by 10-fold external cross-validation. An internal 5-fold cross-validation was also used for the training data set in NN model. The models were compared using regression error characteristic (REC plot and other statistical measures such as relative absolute error (RAE. Sensitivity analysis was also applied to extract useful knowledge from NN model. Results: NN models (with RAE = 78.71 ± 1.16 for BODout and 83.67 ± 1.35 for CODout and MR models (with RAE = 84.40% ± 1.07 for BODout and 88.07 ± 0.80 for CODout indicate different performances and the former was better (P < 0.05 for the prediction of both effluent BOD5 and COD parameters. For the prediction of CODout the NN model with hidden layer size (H = 4 and decay factor = 0.75 ± 0.03 presented the best predictive results. For BODout the H and decay factor were found to be 4 and 0.73 ± 0.03, respectively. TDS was found as the most descriptive influent wastewater characteristics for the prediction of the WSP performance. The REC plots confirmed the NN model performance superiority for both BOD and COD effluent prediction. Conclusion: Modeling the performance of WSP systems using NN models along with sensitivity analysis can offer better

  10. OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

    Science.gov (United States)

    Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

    2017-03-01

    Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

  11. Solubility parameter of drugs for predicting the solubility profile type within a wide polarity range in solvent mixtures.

    Science.gov (United States)

    Peña, M A; Reíllo, A; Escalera, B; Bustamante, P

    2006-09-14

    The solubility enhancement produced by two binary mixtures with a common cosolvent (ethanol-water and ethyl acetate-ethanol) was studied against the solubility parameter of the mixtures (delta1) to characterize different types of solubility profiles. Benzocaine, salicylic acid and acetanilide show a single peak in the least polar mixture (ethanol-ethyl acetate) at delta1=22.59, 21.70 and 20.91 MPa1/2, respectively. Phenacetin displays two solubility maxima, at delta1=25.71 (ethanol-water) and at delta1=23.30 (ethyl acetate-ethanol). Acetanilide shows an inflexion point in ethanol-water instead of a peak, and the sign of the slope does not vary when changing the cosolvent. The solubility profiles were compared to those obtained in dioxane-water, having a solubility parameter range similar to that covered with the common cosolvent system. All the drugs reach a maximum at about 90% dioxane (delta1=23 MPa1/2). A modification of the extended Hildebrand method is applicable for curves with a single maximum whereas a model including the Hildebrand solubility parameter delta1 and the acidic partial solubility parameter delta1a is required to calculate more complex solubility profiles (with inflexion point or two maxima). A single equation was able to fit the solubility curves of all drugs in the common cosolvent system. The polarity of the drug is related to the shape of the solubility profile against the solubility parameter delta1 of the solvent mixtures. The drugs with solubility parameters below 24 MPa1/2 display a single peak in ethanol-ethyl acetate. The drugs with delta2 values above 25 MPa1/2 show two maxima, one in each solvent mixture (ethanol-water and ethanol-ethyl acetate). The position of the maximum in ethanol-ethyl acetate shifts to larger polarity values (higher delta1 values) as the solubility parameter of the drug delta2 increases.

  12. Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience

    Directory of Open Access Journals (Sweden)

    Paolo Bellavista

    2015-07-01

    Full Text Available Nowadays, sensor-rich smartphones potentially enable the harvesting of huge amounts of valuable sensing data in urban environments, by opportunistically involving citizens to play the role of mobile virtual sensors to cover Smart City areas of interest. This paper proposes an in-depth study of the challenging technical issues related to the efficient assignment of Mobile Crowd Sensing (MCS data collection tasks to volunteers in a crowdsensing campaign. In particular, the paper originally describes how to increase the effectiveness of the proposed sensing campaigns through the inclusion of several new facilities, including accurate participant selection algorithms able to profile and predict user mobility patterns, gaming techniques, and timely geo-notification. The reported results show the feasibility of exploiting profiling trends/prediction techniques from volunteers’ behavior; moreover, they quantitatively compare different MCS task assignment strategies based on large-scale and real MCS data campaigns run in the ParticipAct living lab, an ongoing MCS real-world experiment that involved more than 170 students of the University of Bologna for more than one year.

  13. Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

    NARCIS (Netherlands)

    Dijkstra, J.; Kebreab, E.; Mills, J.A.N.; Pellikaan, W.F.; López, S.; Bannink, A.; France, J.

    2007-01-01

    Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product

  14. Validity of the Military Applicant Profile (MAP) for Predicting Early Attrition in Different Educational, Age, and Racial Groups

    Science.gov (United States)

    1982-12-01

    participation in sports , reasons for dropping out of school, personal activities and civilian job experience (Bell, Kristiansen & Seeley, 1974). At...prediction of early Arm attrition through the use of autobiographical information questionaires . Alexandria, VA: US Army Research Institute, Technical Report

  15. Immunohistochemical profiling of caspase signaling pathways predicts clinical response to chemotherapy in primary nodal diffuse large B-cell lymphomas

    NARCIS (Netherlands)

    Muris, JJF; Cillessen, SAGM; Vos, W; van Houdt, IS; Kummer, JA; van Krieken, JHJM; Jiwa, NM; Jansen, PM; Kluin-Nelemans, HC; Ossenkoppele, GJ; Gundy, C; Meijer, CJLM; Oudejans, JJ

    2005-01-01

    We used biopsy specimens of primary nodal diffuse large B-cell lymphoma (DLBCL) to investigate whether the inhibition of caspase 8 and/or 9 apoplosis signaling pathways predicts clinical outcome. Expression levels of cellular FLICE inhibitory protein (c-Flip) and numbers of active caspase 3-positive

  16. Plasma profiles of matrix metalloproteinases and tissue inhibitors of the metalloproteinases predict recurrence of atrial fibrillation following cardioversion.

    Science.gov (United States)

    Mukherjee, Rupak; Akar, Joseph G; Wharton, J Marcus; Adams, Deborah K; McClure, Catherine D; Stroud, Robert E; Rice, Allison D; DeSantis, Stacia M; Spinale, Francis G; Gold, Michael R

    2013-08-01

    Atrial fibrosis is considered to contribute to atrial fibrillation (AF) recurrence following cardioversion. This study tested the hypothesis that circulating levels of matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs) can predict AF recurrence postcardioversion. Precardioversion plasma samples (n = 82) were assayed for MMPs (eight types), TIMPs (all four types), N-terminus pro B-type natriuretic peptide, and high-sensitivity C-reactive protein levels. Patients were followed for AF recurrence postcardioversion. Despite 100 % restoration of sinus rhythm, 36 (44 %) reverted to AF within 3 months. Left atrial volume was increased in patients in whom AF recurred. Precardioversion MMP-9 was higher and TIMP-4 lower with AF recurrence. MMP-9, MMP-3, and TIMP-4 independently predicted AF recurrence. In multivariate analysis, combination of MMP-9, MMP-3, and TIMP-4 increased prediction of AF recurrence. Circulating levels of MMPs and TIMPs predict AF recurrence postcardioversion and may be used in a novel biomarker panel to guide AF stratification and therapy.

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

    Science.gov (United States