AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159

Approximated affine projection algorithm for feedback cancellation in hearing aids.

PubMed

Lee, Sangmin; Kim, In-Young; Park, Young-Cheol

2007-09-01

We propose an approximated affine projection (AP) algorithm for feedback cancellation in hearing aids. It is based on the conventional approach using the Gauss-Seidel (GS) iteration, but provides more stable convergence behaviour even with small step sizes. In the proposed algorithm, a residue of the weighted error vector, instead of the current error sample, is used to provide stable convergence. A new learning rate control scheme is also applied to the proposed algorithm to prevent signal cancellation and system instability. The new scheme determines step size in proportion to the prediction factor of the input, so that adaptation is inhibited whenever tone-like signals are present in the input. Simulation results verified the efficiency of the proposed algorithm.

AVQS: attack route-based vulnerability quantification scheme for smart grid.

PubMed

Ko, Jongbin; Lim, Hyunwoo; Lee, Seokjun; Shon, Taeshik

2014-01-01

A smart grid is a large, consolidated electrical grid system that includes heterogeneous networks and systems. Based on the data, a smart grid system has a potential security threat in its network connectivity. To solve this problem, we develop and apply a novel scheme to measure the vulnerability in a smart grid domain. Vulnerability quantification can be the first step in security analysis because it can help prioritize the security problems. However, existing vulnerability quantification schemes are not suitable for smart grid because they do not consider network vulnerabilities. We propose a novel attack route-based vulnerability quantification scheme using a network vulnerability score and an end-to-end security score, depending on the specific smart grid network environment to calculate the vulnerability score for a particular attack route. To evaluate the proposed approach, we derive several attack scenarios from the advanced metering infrastructure domain. The experimental results of the proposed approach and the existing common vulnerability scoring system clearly show that we need to consider network connectivity for more optimized vulnerability quantification.

PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

PubMed

Tang, Yat T; Marshall, Garland R

2011-02-28

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Numerical scoring for the Classic BILAG index.

PubMed

Cresswell, Lynne; Yee, Chee-Seng; Farewell, Vernon; Rahman, Anisur; Teh, Lee-Suan; Griffiths, Bridget; Bruce, Ian N; Ahmad, Yasmeen; Prabu, Athiveeraramapandian; Akil, Mohammed; McHugh, Neil; Toescu, Veronica; D'Cruz, David; Khamashta, Munther A; Maddison, Peter; Isenberg, David A; Gordon, Caroline

2009-12-01

To develop an additive numerical scoring scheme for the Classic BILAG index. SLE patients were recruited into this multi-centre cross-sectional study. At every assessment, data were collected on disease activity and therapy. Logistic regression was used to model an increase in therapy, as an indicator of active disease, by the Classic BILAG score in eight systems. As both indicate inactivity, scores of D and E were set to 0 and used as the baseline in the fitted model. The coefficients from the fitted model were used to determine the numerical values for Grades A, B and C. Different scoring schemes were then compared using receiver operating characteristic (ROC) curves. Validation analysis was performed using assessments from a single centre. There were 1510 assessments from 369 SLE patients. The currently used coding scheme (A = 9, B = 3, C = 1 and D/E = 0) did not fit the data well. The regression model suggested three possible numerical scoring schemes: (i) A = 11, B = 6, C = 1 and D/E = 0; (ii) A = 12, B = 6, C = 1 and D/E = 0; and (iii) A = 11, B = 7, C = 1 and D/E = 0. These schemes produced comparable ROC curves. Based on this, A = 12, B = 6, C = 1 and D/E = 0 seemed a reasonable and practical choice. The validation analysis suggested that although the A = 12, B = 6, C = 1 and D/E = 0 coding is still reasonable, a scheme with slightly less weighting for B, such as A = 12, B = 5, C = 1 and D/E = 0, may be more appropriate. A reasonable additive numerical scoring scheme based on treatment decision for the Classic BILAG index is A = 12, B = 5, C = 1, D = 0 and E = 0.

Numerical scoring for the Classic BILAG index

PubMed Central

Cresswell, Lynne; Yee, Chee-Seng; Farewell, Vernon; Rahman, Anisur; Teh, Lee-Suan; Griffiths, Bridget; Bruce, Ian N.; Ahmad, Yasmeen; Prabu, Athiveeraramapandian; Akil, Mohammed; McHugh, Neil; Toescu, Veronica; D’Cruz, David; Khamashta, Munther A.; Maddison, Peter; Isenberg, David A.

2009-01-01

Objective. To develop an additive numerical scoring scheme for the Classic BILAG index. Methods. SLE patients were recruited into this multi-centre cross-sectional study. At every assessment, data were collected on disease activity and therapy. Logistic regression was used to model an increase in therapy, as an indicator of active disease, by the Classic BILAG score in eight systems. As both indicate inactivity, scores of D and E were set to 0 and used as the baseline in the fitted model. The coefficients from the fitted model were used to determine the numerical values for Grades A, B and C. Different scoring schemes were then compared using receiver operating characteristic (ROC) curves. Validation analysis was performed using assessments from a single centre. Results. There were 1510 assessments from 369 SLE patients. The currently used coding scheme (A = 9, B = 3, C = 1 and D/E = 0) did not fit the data well. The regression model suggested three possible numerical scoring schemes: (i) A = 11, B = 6, C = 1 and D/E = 0; (ii) A = 12, B = 6, C = 1 and D/E = 0; and (iii) A = 11, B = 7, C = 1 and D/E = 0. These schemes produced comparable ROC curves. Based on this, A = 12, B = 6, C = 1 and D/E = 0 seemed a reasonable and practical choice. The validation analysis suggested that although the A = 12, B = 6, C = 1 and D/E = 0 coding is still reasonable, a scheme with slightly less weighting for B, such as A = 12, B = 5, C = 1 and D/E = 0, may be more appropriate. Conclusions. A reasonable additive numerical scoring scheme based on treatment decision for the Classic BILAG index is A = 12, B = 5, C = 1, D = 0 and E = 0. PMID:19779027

Al7CX (X=Li-Cs) clusters: Stability and the prospect for cluster materials

NASA Astrophysics Data System (ADS)

Ashman, C.; Khanna, S. N.; Pederson, M. R.; Kortus, J.

2000-12-01

Al7C clusters, recently found to have a high-electron affinity and exceptional stability, are shown to form ionic molecules when combined with alkali-metal atoms. Our studies, based on an ab initio gradient-corrected density-functional scheme, show that Al7CX (X=Li-Cs) clusters have a very low-electron affinity and a high-ionization potential. When combined, the two- and four-atom composite clusters of Al7CLi units leave the Al7C clusters almost intact. Preliminary studies indicate that Al7CLi may be suitable to form cluster-based materials.

TS-Chemscore, a Target-Specific Scoring Function, Significantly Improves the Performance of Scoring in Virtual Screening.

PubMed

Wang, Wen-Jing; Huang, Qi; Zou, Jun; Li, Lin-Li; Yang, Sheng-Yong

2015-07-01

Most of the scoring functions currently used in structure-based drug design belong to 'universal' scoring functions, which often give a poor correlation between the calculated scores and experimental binding affinities. In this investigation, we proposed a simple strategy to construct target-specific scoring functions based on known 'universal' scoring functions. This strategy was applied to Chemscore, a widely used empirical scoring function, which led to a new scoring function, termed TS-Chemscore. TS-Chemscore was validated on 14 protein targets, which cover a wide range of biological target categories. The results showed that TS-Chemscore significantly improved the correlation between the calculated scores and experimental binding affinities compared with the original Chemscore. TS-Chemscore was then applied in virtual screening to retrieve novel JAK3 and YopH inhibitors. Top 30 compounds for each target were selected for experimental validation. Six active compounds for JAK3 and four for YopH were obtained. These compounds were out of the lists of top 30 compounds sorted by Chemscore. Collectively, TS-Chemscore established in this study showed a better performance in virtual screening than its counterpart Chemscore. © 2014 John Wiley & Sons A/S.

AVQS: Attack Route-Based Vulnerability Quantification Scheme for Smart Grid

PubMed Central

Lim, Hyunwoo; Lee, Seokjun; Shon, Taeshik

2014-01-01

A smart grid is a large, consolidated electrical grid system that includes heterogeneous networks and systems. Based on the data, a smart grid system has a potential security threat in its network connectivity. To solve this problem, we develop and apply a novel scheme to measure the vulnerability in a smart grid domain. Vulnerability quantification can be the first step in security analysis because it can help prioritize the security problems. However, existing vulnerability quantification schemes are not suitable for smart grid because they do not consider network vulnerabilities. We propose a novel attack route-based vulnerability quantification scheme using a network vulnerability score and an end-to-end security score, depending on the specific smart grid network environment to calculate the vulnerability score for a particular attack route. To evaluate the proposed approach, we derive several attack scenarios from the advanced metering infrastructure domain. The experimental results of the proposed approach and the existing common vulnerability scoring system clearly show that we need to consider network connectivity for more optimized vulnerability quantification. PMID:25152923

On the vanishing couplings in ADE affine Toda field theories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saitoh, Y.; Shimada, T.

In this paper, the authors show that certain vanishing couplins in the ADE affine Toda field theories remain vanishing even after higher-order corrections are included. This is a requisite property for the Lagrangian formulation of the theory. The authors develop a new perturbative formulation and treat affine Toda field theories as a massless theory with exponential interaction terms. The authors shown that the nonrenormalization comes from the Dynkin automorphism of the Lie algebra associated with these theories. A charge balance conditions plays an important role in our scheme. The all-order nonrenormalization of vanishing couplings in [bar A][sub n] affine Todamore » field theory is also proved in a standard massive scheme.« less

Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

PubMed

Catana, Cornel; Stouten, Pieter F W

2007-01-01

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need. In the present work, three such customized scoring functions were developed using a set of 129 high-resolution protein-ligand crystal structures with measured Ki values. The functions were parametrized using N-PLS (N-way partial least squares), a multivariate technique well-known in the 3D quantitative structure-activity relationship field. A modest correlation between observed and calculated pKi values using a standard scoring function (r2 = 0.5) could be improved to 0.8 when a customized scoring function was applied. To mimic a more realistic scenario, a second scoring function was developed, not based on crystal structures but exclusively on several binding poses generated with the Flo+ docking program. Finally, a validation study was conducted by generating a third scoring function with 99 randomly selected complexes from the 129 as a training set and predicting pKi values for a test set that comprised the remaining 30 complexes. Training and test set r2 values were 0.77 and 0.78, respectively. These results indicate that, even without direct structural information, predictive customized scoring functions can be developed using N-PLS, and this approach holds significant potential as a general procedure for predicting binding affinity on the basis of in silico docking.

Bidirectional Elastic Image Registration Using B-Spline Affine Transformation

PubMed Central

Gu, Suicheng; Meng, Xin; Sciurba, Frank C.; Wang, Chen; Kaminski, Naftali; Pu, Jiantao

2014-01-01

A registration scheme termed as B-spline affine transformation (BSAT) is presented in this study to elastically align two images. We define an affine transformation instead of the traditional translation at each control point. Mathematically, BSAT is a generalized form of the affine transformation and the traditional B-Spline transformation (BST). In order to improve the performance of the iterative closest point (ICP) method in registering two homologous shapes but with large deformation, a bi-directional instead of the traditional unidirectional objective / cost function is proposed. In implementation, the objective function is formulated as a sparse linear equation problem, and a sub-division strategy is used to achieve a reasonable efficiency in registration. The performance of the developed scheme was assessed using both two-dimensional (2D) synthesized dataset and three-dimensional (3D) volumetric computed tomography (CT) data. Our experiments showed that the proposed B-spline affine model could obtain reasonable registration accuracy. PMID:24530210

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

PubMed

Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

2015-10-01

Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

Assessing the impact of a cattle risk-based trading scheme on the movement of bovine tuberculosis infected animals in England and Wales.

PubMed

Adkin, A; Brouwer, A; Downs, S H; Kelly, L

2016-01-01

The adoption of bovine tuberculosis (bTB) risk-based trading (RBT) schemes has the potential to reduce the risk of bTB spread. However, any scheme will have cost implications that need to be balanced against its likely success in reducing bTB. This paper describes the first stochastic quantitative model assessing the impact of the implementation of a cattle risk-based trading scheme to inform policy makers and contribute to cost-benefit analyses. A risk assessment for England and Wales was developed to estimate the number of infected cattle traded using historic movement data recorded between July 2010 and June 2011. Three scenarios were implemented: cattle traded with no RBT scheme in place, voluntary provision of the score and a compulsory, statutory scheme applying a bTB risk score to each farm. For each scenario, changes in trade were estimated due to provision of the risk score to potential purchasers. An estimated mean of 3981 bTB infected animals were sold to purchasers with no RBT scheme in place in one year, with 90% confidence the true value was between 2775 and 5288. This result is dependent on the estimated between herd prevalence used in the risk assessment which is uncertain. With the voluntary provision of the risk score by farmers, on average, 17% of movements was affected (purchaser did not wish to buy once the risk score was available), with a reduction of 23% in infected animals being purchased initially. The compulsory provision of the risk score in a statutory scheme resulted in an estimated mean change to 26% of movements, with a reduction of 37% in infected animals being purchased initially, increasing to a 53% reduction in infected movements from higher risk sellers (score 4 and 5). The estimated mean reduction in infected animals being purchased could be improved to 45% given a 10% reduction in risky purchase behaviour by farmers which may be achieved through education programmes, or to an estimated mean of 49% if a rule was implemented preventing farmers from the purchase of animals of higher risk than their own herd. Given voluntary trials currently taking place of a trading scheme, recommendations for future work include the monitoring of initial uptake and changes in the purchase patterns of farmers. Such data could be used to update the risk assessment to reduce uncertainty associated with model estimates. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Characterization of protein--DNA interactions using surface plasmon resonance spectroscopy with various assay schemes.

PubMed

Teh, Huey Fang; Peh, Wendy Y X; Su, Xiaodi; Thomsen, Jane S

2007-02-27

Specific protein-DNA interactions play a central role in transcription and other biological processes. A comprehensive characterization of protein-DNA interactions should include information about binding affinity, kinetics, sequence specificity, and binding stoichiometry. In this study, we have used surface plasmon resonance spectroscopy (SPR) to study the interactions between human estrogen receptors (ER, alpha and beta subtypes) and estrogen response elements (ERE), with four assay schemes. First, we determined the sequence-dependent receptors' binding capacity by monitoring the binding of ER to various ERE sequences immobilized on a sensor surface (assay format denoted as the direct assay). Second, we screened the relative affinity of ER for various ERE sequences using a competition assay, in which the receptors bind to an ERE-immobilized surface in the presence of competitor ERE sequences. Third, we monitored the assembly of ER-ERE complexes on a SPR surface and thereafter the removal and/or dissociation of the ER (assay scheme denoted as the dissociation assay) to determine the binding stoichiometry. Last, a sandwich assay (ER binding to ERE followed by anti-ER recognition of a specific ER subtype) was performed in an effort to understand how ERalpha and ERbeta may associate and compete when binding to the DNA. With these assay schemes, we reaffirmed that (1) ERalpha is more sensitive than ERbeta to base pair change(s) in the consensus ERE, (2) ERalpha and ERbeta form a heterodimer when they bind to the consensus ERE, and (3) the binding stoichiometry of both ERalpha- and ERbeta-ERE complexes is dependent on salt concentration. With this study, we demonstrate the versatility of the SPR analysis. With the involvement of various assay arrangements, the SPR analysis can be further extended to more than kinetics and affinity study.

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

NASA Astrophysics Data System (ADS)

Duan, Rui; Xu, Xianjin; Zou, Xiaoqin

2018-01-01

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

Understanding latent structures of clinical information logistics: A bottom-up approach for model building and validating the workflow composite score.

PubMed

Esdar, Moritz; Hübner, Ursula; Liebe, Jan-David; Hüsers, Jens; Thye, Johannes

2017-01-01

Clinical information logistics is a construct that aims to describe and explain various phenomena of information provision to drive clinical processes. It can be measured by the workflow composite score, an aggregated indicator of the degree of IT support in clinical processes. This study primarily aimed to investigate the yet unknown empirical patterns constituting this construct. The second goal was to derive a data-driven weighting scheme for the constituents of the workflow composite score and to contrast this scheme with a literature based, top-down procedure. This approach should finally test the validity and robustness of the workflow composite score. Based on secondary data from 183 German hospitals, a tiered factor analytic approach (confirmatory and subsequent exploratory factor analysis) was pursued. A weighting scheme, which was based on factor loadings obtained in the analyses, was put into practice. We were able to identify five statistically significant factors of clinical information logistics that accounted for 63% of the overall variance. These factors were "flow of data and information", "mobility", "clinical decision support and patient safety", "electronic patient record" and "integration and distribution". The system of weights derived from the factor loadings resulted in values for the workflow composite score that differed only slightly from the score values that had been previously published based on a top-down approach. Our findings give insight into the internal composition of clinical information logistics both in terms of factors and weights. They also allowed us to propose a coherent model of clinical information logistics from a technical perspective that joins empirical findings with theoretical knowledge. Despite the new scheme of weights applied to the calculation of the workflow composite score, the score behaved robustly, which is yet another hint of its validity and therefore its usefulness. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

PubMed

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

PubMed Central

Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-01-01

Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

PubMed Central

Brender, Jeffrey R.; Zhang, Yang

2015-01-01

The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies. PMID:26506533

Importance of ligand reorganization free energy in protein-ligand binding-affinity prediction.

PubMed

Yang, Chao-Yie; Sun, Haiying; Chen, Jianyong; Nikolovska-Coleska, Zaneta; Wang, Shaomeng

2009-09-30

Accurate prediction of the binding affinities of small-molecule ligands to their biological targets is fundamental for structure-based drug design but remains a very challenging task. In this paper, we have performed computational studies to predict the binding models of 31 small-molecule Smac (the second mitochondria-derived activator of caspase) mimetics to their target, the XIAP (X-linked inhibitor of apoptosis) protein, and their binding affinities. Our results showed that computational docking was able to reliably predict the binding models, as confirmed by experimentally determined crystal structures of some Smac mimetics complexed with XIAP. However, all the computational methods we have tested, including an empirical scoring function, two knowledge-based scoring functions, and MM-GBSA (molecular mechanics and generalized Born surface area), yield poor to modest prediction for binding affinities. The linear correlation coefficient (r(2)) value between the predicted affinities and the experimentally determined affinities was found to be between 0.21 and 0.36. Inclusion of ensemble protein-ligand conformations obtained from molecular dynamic simulations did not significantly improve the prediction. However, major improvement was achieved when the free-energy change for ligands between their free- and bound-states, or "ligand-reorganization free energy", was included in the MM-GBSA calculation, and the r(2) value increased from 0.36 to 0.66. The prediction was validated using 10 additional Smac mimetics designed and evaluated by an independent group. This study demonstrates that ligand reorganization free energy plays an important role in the overall binding free energy between Smac mimetics and XIAP. This term should be evaluated for other ligand-protein systems and included in the development of new scoring functions. To our best knowledge, this is the first computational study to demonstrate the importance of ligand reorganization free energy for the prediction of protein-ligand binding free energy.

Hybrid Steered Molecular Dynamics-Docking: An Efficient Solution to the Problem of Ranking Inhibitor Affinities Against a Flexible Drug Target.

PubMed

Whalen, Katie L; Chang, Kevin M; Spies, M Ashley

2011-05-16

Existing techniques which attempt to predict the affinity of protein-ligand interactions have demonstrated a direct relationship between computational cost and prediction accuracy. We present here the first application of a hybrid ensemble docking and steered molecular dynamics scheme (with a minimized computational cost), which achieves a binding affinity rank-ordering of ligands with a Spearman correlation coefficient of 0.79 and an RMS error of 0.7 kcal/mol. The scheme, termed Flexible Enzyme Receptor Method by Steered Molecular Dynamics (FERM-SMD), is applied to an in-house collection of 17 validated ligands of glutamate racemase. The resulting improved accuracy in affinity prediction allows elucidation of the key structural components of a heretofore unreported glutamate racemase inhibitor (K(i) = 9 µM), a promising new lead in the development of antibacterial therapeutics.

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin

2016-03-01

Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.

A Novel Algorithm for Detecting Protein Complexes with the Breadth First Search

PubMed Central

Tang, Xiwei; Wang, Jianxin; Li, Min; He, Yiming; Pan, Yi

2014-01-01

Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes from the weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the weighted density, ClusterBFS detects protein complexes of the weighted network by the breadth first search algorithm, which originates from a given seed protein used as starting-point. The experimental results show that ClusterBFS performs significantly better than the other computational approaches in terms of the identification of protein complexes. PMID:24818139

Scoring schemes of palindrome clusters for more sensitive prediction of replication origins in herpesviruses

PubMed Central

Chew, David S. H.; Choi, Kwok Pui; Leung, Ming-Ying

2005-01-01

Many empirical studies show that there are unusual clusters of palindromes, closely spaced direct and inverted repeats around the replication origins of herpesviruses. In this paper, we introduce two new scoring schemes to quantify the spatial abundance of palindromes in a genomic sequence. Based on these scoring schemes, a computational method to predict the locations of replication origins is developed. When our predictions are compared with 39 known or annotated replication origins in 19 herpesviruses, close to 80% of the replication origins are located within 2% of the genome length. A list of predicted locations of replication origins in all the known herpesviruses with complete genome sequences is reported. PMID:16141192

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

PubMed

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

NASA Astrophysics Data System (ADS)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.

PubMed

Chen, Fu; Sun, Huiyong; Wang, Junmei; Zhu, Feng; Liu, Hui; Wang, Zhe; Lei, Tailong; Li, Youyong; Hou, Tingjun

2018-06-21

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (ϵ in ). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GBGBn1 model with ϵ in = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GBGBn1 model distinguished the near-native binding structures within the top 10 decoys for 118 out of the 149 protein-RNA systems (79.2%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Computational technique for stepwise quantitative assessment of equation correctness

NASA Astrophysics Data System (ADS)

Othman, Nuru'l Izzah; Bakar, Zainab Abu

2017-04-01

Many of the computer-aided mathematics assessment systems that are available today possess the capability to implement stepwise correctness checking of a working scheme for solving equations. The computational technique for assessing the correctness of each response in the scheme mainly involves checking the mathematical equivalence and providing qualitative feedback. This paper presents a technique, known as the Stepwise Correctness Checking and Scoring (SCCS) technique that checks the correctness of each equation in terms of structural equivalence and provides quantitative feedback. The technique, which is based on the Multiset framework, adapts certain techniques from textual information retrieval involving tokenization, document modelling and similarity evaluation. The performance of the SCCS technique was tested using worked solutions on solving linear algebraic equations in one variable. 350 working schemes comprising of 1385 responses were collected using a marking engine prototype, which has been developed based on the technique. The results show that both the automated analytical scores and the automated overall scores generated by the marking engine exhibit high percent agreement, high correlation and high degree of agreement with manual scores with small average absolute and mixed errors.

In silico optimization of a fragment-based hit yields biologically active, high-efficiency inhibitors for glutamate racemase.

PubMed

Whalen, Katie L; Chau, Anthony C; Spies, M Ashley

2013-10-01

A novel lead compound for inhibition of the antibacterial drug target, glutamate racemase (GR), was optimized for both ligand efficiency and lipophilic efficiency. A previously developed hybrid molecular dynamics-docking and scoring scheme, FERM-SMD, was used to predict relative potencies of potential derivatives prior to chemical synthesis. This scheme was successful in distinguishing between high- and low-affinity binders with minimal experimental structural information, saving time and resources in the process. In vitro potency was increased approximately fourfold against GR from the model organism, B. subtilis. Lead derivatives show two- to fourfold increased antimicrobial potency over the parent scaffold. In addition, specificity toward B. subtilis over E. coli and S. aureus depends on the substituent added to the parent scaffold. Finally, insight was gained into the capacity for these compounds to reach the target enzyme in vivo using a bacterial cell wall lysis assay. The outcome of this study is a novel small-molecule inhibitor of GR with the following characteristics: Ki=2.5 μM, LE=0.45 kcal mol(-1) atom(-1), LiPE=6.0, MIC50=260 μg mL(-1) against B. subtilis, EC50, lysis=520 μg mL(-1) against B. subtilis. Copyright © 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.

Thermodynamic Bounds on the Ultra- and Infra-affinity of Hsp70 for Its Substrates

NASA Astrophysics Data System (ADS)

Nguyen, Basile; Hartich, David; Seifert, Udo; Rios, Paolo De Los

2017-07-01

The 70 kDa Heat Shock Proteins Hsp70 have several essential functions in living systems, such as protecting cells against protein aggregation, assisting protein folding, remodeling protein complexes and driving the translocation into organelles. These functions require high affinity for non-specific amino-acid sequences that are ubiquitous in proteins. It has been recently shown that this high affinity, called ultra-affinity, depends on a process driven out of equilibrium by ATP hydrolysis. Here we establish the thermodynamic bounds for ultra-affinity, and further show that the same reaction scheme can in principle be used both to strengthen and to weaken affinities (leading in this case to infra-affinity). We show that cofactors are essential to achieve affinity beyond the equilibrium range. Finally, biological implications are discussed.

Stroke prevention with oral anticoagulation in older people with atrial fibrillation - a pragmatic approach.

PubMed

Ali, Ali; Bailey, Claire; Abdelhafiz, Ahmed H

2012-08-01

With advancing age, the prevalence of both stroke and non valvular atrial fibrillation (NVAF) is increasing. NVAF in old age has a high embolic potential if not anticoagulated. Oral anticoagulation therapy is cost effective in older people with NVAF due to their high base line stroke risk. The current stroke and bleeding risk scoring schemes have been based on complex scoring systems that are difficult to apply in clinical practice. Both scoring schemes include similar risk factors for ischemic and bleeding events which may lead to confusion in clinical decision making to balance the risks of bleeding against the risks of stroke, thereby limiting the applicability of such schemes. The difficulty in application of such schemes combined with physicians' fear of inducing bleeding complications has resulted in under use of anticoagulation therapy in older people. As older people (≥75 years) with NVAF are all at high risk of stroke, we are suggesting a pragmatic approach based on a yes/no decision rather than a risk scoring stratification which involves an opt out rather an opt in approach unless there is a contraindication for oral anticoagulation. Antiplatelet agents should not be an alternative option for antithrombotic treatment in older people with NVAF due to lack of efficacy and the potential of being used as an excuse of not prescribing anticoagulation. Bleeding risk should be assessed on individual basis and the decision to anticoagulate should include patients' views.

Stroke Prevention with Oral Anticoagulation in Older People with Atrial Fibrillation - A Pragmatic Approach

PubMed Central

Ali, Ali; Bailey, Claire; Abdelhafiz, Ahmed H

2012-01-01

With advancing age, the prevalence of both stroke and non valvular atrial fibrillation (NVAF) is increasing. NVAF in old age has a high embolic potential if not anticoagulated. Oral anticoagulation therapy is cost effective in older people with NVAF due to their high base line stroke risk. The current stroke and bleeding risk scoring schemes have been based on complex scoring systems that are difficult to apply in clinical practice. Both scoring schemes include similar risk factors for ischemic and bleeding events which may lead to confusion in clinical decision making to balance the risks of bleeding against the risks of stroke, thereby limiting the applicability of such schemes. The difficulty in application of such schemes combined with physicians’ fear of inducing bleeding complications has resulted in under use of anticoagulation therapy in older people. As older people (≥75 years) with NVAF are all at high risk of stroke, we are suggesting a pragmatic approach based on a yes/no decision rather than a risk scoring stratification which involves an opt out rather an opt in approach unless there is a contraindication for oral anticoagulation. Antiplatelet agents should not be an alternative option for antithrombotic treatment in older people with NVAF due to lack of efficacy and the potential of being used as an excuse of not prescribing anticoagulation. Bleeding risk should be assessed on individual basis and the decision to anticoagulate should include patients’ views. PMID:23185715

Performance of machine-learning scoring functions in structure-based virtual screening.

PubMed

Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

2017-04-25

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

PubMed

Xiao, Shijie; Xu, Dong; Wu, Jianxin

2015-10-01

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data. Specifically, by introducing a specially designed regularizer to the low-rank representation method, we penalize the corresponding reconstruction coefficients related to the situations where a face is reconstructed by using face images from other subjects or by using itself. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. Moreover, we also develop a new distance metric learning method called ambiguously supervised structural metric learning by using weakly supervised information to seek a discriminative distance metric. Hence, another discriminative affinity matrix can be obtained using the similarity matrix (i.e., the kernel matrix) based on the Mahalanobis distances of the data. Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Comprehensive experiments demonstrate the effectiveness of our approach.

Cell behavior on gallium nitride surfaces: peptide affinity attachment versus covalent functionalization.

PubMed

Foster, Corey M; Collazo, Ramon; Sitar, Zlatko; Ivanisevic, Albena

2013-07-02

Gallium nitride is a wide band gap semiconductor that demonstrates a unique set of optical and electrical properties as well as aqueous stability and biocompatibility. This combination of properties makes gallium nitride a strong candidate for use in chemical and biological applications such as sensors and neural interfaces. Molecular modification can be used to enhance the functionality and properties of the gallium nitride surface. Here, gallium nitride surfaces were functionalized with a PC12 cell adhesion promoting peptide using covalent and affinity driven attachment methods. The covalent scheme proceeded by Grignard reaction and olefin metathesis while the affinity driven scheme utilized the recognition peptide isolated through phage display. This study shows that the method of attaching the adhesion peptide influences PC12 cell adhesion and differentiation as measured by cell density and morphological analysis. Covalent attachment promoted monolayer and dispersed cell adhesion while affinity driven attachment promoted multilayer cell agglomeration. Higher cell density was observed on surfaces modified using the recognition peptide. The results suggest that the covalent and affinity driven attachment methods are both suitable for promoting PC12 cell adhesion to the gallium nitride surface, though each method may be preferentially suited for distinct applications.

Adverse Selection in Community Based Health Insurance among Informal Workers in Bangladesh: An EQ-5D Assessment

PubMed Central

Sarker, Abdur Razzaque; Sultana, Marufa; Chakrovorty, Sanchita; Khan, Jahangir A. M.

2018-01-01

Community-based Health Insurance (CBHI) schemes are recommended for providing financial risk protection to low-income informal workers in Bangladesh. We assessed the problem of adverse selection in a pilot CBHI scheme in this context. In total, 1292 (646 insured and 646 uninsured) respondents were surveyed using the Bengali version of the EuroQuol-5 dimensions (EQ-5D) questionnaire for assessing their health status. The EQ-5D scores were estimated using available regional tariffs. Multiple logistic regression was applied for predicting the association between health status and CBHI scheme enrolment. A higher number of insured reported problems in mobility (7.3%; p = 0.002); self-care (7.1%; p = 0.000) and pain and discomfort (7.7%; p = 0.005) than uninsured. The average EQ-5D score was significantly lower among the insured (0.704) compared to the uninsured (0.749). The regression analysis showed that those who had a problem in mobility (OR = 1.65; 95% CI: 1.25–2.17); self-care (OR = 2.29; 95% CI: 1.62–3.25) and pain and discomfort (OR = 1.43; 95% CI: 1.13–1.81) were more likely to join the scheme. Individuals with higher EQ-5D scores (OR = 0.46; 95% CI: 0.31–0.69) were less likely to enroll in the scheme. Given that adverse selection was evident in the pilot CBHI scheme, there should be consideration of this problem when planning scale-up of these kind of schemes. PMID:29385072

Atomistic models for free energy evaluation of drug binding to membrane proteins.

PubMed

Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y

2011-01-01

The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.

Student-Centered Reliability, Concurrent Validity and Instructional Sensitivity in Scoring of Students' Concept Maps in a University Science Laboratory

ERIC Educational Resources Information Center

Kaya, Osman Nafiz; Kilic, Ziya

2004-01-01

Student-centered approach of scoring the concept maps consisted of three elements namely symbol system, individual portfolio and scoring scheme. We scored student-constructed concept maps based on 5 concept map criteria: validity of concepts, adequacy of propositions, significance of cross-links, relevancy of examples, and interconnectedness. With…

Slit Lamp-Based Ocular Scoring Systems in Toxicology and Drug Development: A Literature Survey.

PubMed

Eaton, Joshua Seth; Miller, Paul E; Bentley, Ellison; Thomasy, Sara M; Murphy, Christopher J

2017-12-01

To present a survey of the features of published slit lamp-based scoring systems and their applicability in the context of modern ocular toxicology and drug development. References describing original or modified slit lamp-based scoring systems for human or veterinary clinical patients or in investigative or toxicologic research were collected following a comprehensive literature review using textbooks and online publication searches. Each system's indications and features were compiled to facilitate comparison. Literature review identified 138 original or modified scoring systems. Most (48%) were published for evaluation of the ocular surface, 34% for the general anterior segment, and 18% for the lens. Most systems were described for assessment of human patients (50%) and small albino laboratory species such as rabbits (19%), rats (12%), and mice (8%). Systems described for pigmented laboratory species and for larger species such as dogs, cats, pigs, and nonhuman primates (NHPs) were comparatively underrepresented. No systems described a lens scoring scheme specific to the dog, cat, pig, or NHP. Scoring schemes for aqueous and vitreous cells were infrequently described for laboratory species. Many slit lamp-based scoring systems have been published, but the features of each differ and complicate translation of findings between different species. Use and interpretation of any scoring system in toxicology and drug development must be done with awareness of the limitations of the system being used.

Performance of machine-learning scoring functions in structure-based virtual screening

PubMed Central

Wójcikowski, Maciej; Ballester, Pedro J.; Siedlecki, Pawel

2017-01-01

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and −0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary). PMID:28440302

A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

PubMed

Wang, Jianji; Zheng, Nanning

2013-09-01

Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

The Whereabouts of Flower Visitors: Contrasting Land-Use Preferences Revealed by a Country-Wide Survey Based on Citizen Science

PubMed Central

Deguines, Nicolas; Julliard, Romain; de Flores, Mathieu; Fontaine, Colin

2012-01-01

Background In the past decade, accumulating evidence of pollinator decline has raised concerns regarding the functioning of terrestrial ecosystems and the sustainability of crop production. Although land-use changes have been advanced as the major causes, the affinities of most wild pollinators with the main land-use types remain unknown. Filling this gap in our knowledge is a prerequisite to improving conservation and management programmes. Methodology/Principal Findings We estimated the affinity of flower visitors with urban, agricultural and natural land-uses using data from a country-wide scale monitoring scheme based on citizen science (Spipoll). We tested whether the affinities differed among insect orders and according to insect frequency (frequent or infrequent). Our results indicate that the affinities with the three land-use types differed among insect orders. Apart from Hymenopterans, which appeared tolerant to the different land-uses, all flower visitors presented a negative affinity with urban areas and a positive affinity with agricultural and natural areas. Additionally, infrequent taxa displayed a lower affinity with urban areas and a higher affinity with natural areas than did frequent taxa. Within frequent taxa, Hymenoptera and Coleoptera included specialists of the three land-use types whereas Diptera and Lepidoptera contained specialists of all but urban areas. Conclusions/Significance Our approach allowed the first standardised evaluation of the affinity of flower visitors with the main land-use types across a broad taxonomical range and a wide geographic scope. Our results suggest that the most detrimental land-use change for flower visitor communities is urbanisation. Moreover, our findings highlight the fact that agricultural areas have the potential to host highly diverse pollinator communities. We suggest that policy makers should, therefore, focus on the implementation of pollinator-friendly practices in agricultural lands. This may be a win-win strategy, as both biodiversity and crop production may benefit from healthier communities of flower visitors in these areas. PMID:23029262

The whereabouts of flower visitors: contrasting land-use preferences revealed by a country-wide survey based on citizen science.

PubMed

Deguines, Nicolas; Julliard, Romain; de Flores, Mathieu; Fontaine, Colin

2012-01-01

In the past decade, accumulating evidence of pollinator decline has raised concerns regarding the functioning of terrestrial ecosystems and the sustainability of crop production. Although land-use changes have been advanced as the major causes, the affinities of most wild pollinators with the main land-use types remain unknown. Filling this gap in our knowledge is a prerequisite to improving conservation and management programmes. We estimated the affinity of flower visitors with urban, agricultural and natural land-uses using data from a country-wide scale monitoring scheme based on citizen science (Spipoll). We tested whether the affinities differed among insect orders and according to insect frequency (frequent or infrequent). Our results indicate that the affinities with the three land-use types differed among insect orders. Apart from Hymenopterans, which appeared tolerant to the different land-uses, all flower visitors presented a negative affinity with urban areas and a positive affinity with agricultural and natural areas. Additionally, infrequent taxa displayed a lower affinity with urban areas and a higher affinity with natural areas than did frequent taxa. Within frequent taxa, Hymenoptera and Coleoptera included specialists of the three land-use types whereas Diptera and Lepidoptera contained specialists of all but urban areas. Our approach allowed the first standardised evaluation of the affinity of flower visitors with the main land-use types across a broad taxonomical range and a wide geographic scope. Our results suggest that the most detrimental land-use change for flower visitor communities is urbanisation. Moreover, our findings highlight the fact that agricultural areas have the potential to host highly diverse pollinator communities. We suggest that policy makers should, therefore, focus on the implementation of pollinator-friendly practices in agricultural lands. This may be a win-win strategy, as both biodiversity and crop production may benefit from healthier communities of flower visitors in these areas.

Edge-based nonlinear diffusion for finite element approximations of convection-diffusion equations and its relation to algebraic flux-correction schemes.

PubMed

Barrenechea, Gabriel R; Burman, Erik; Karakatsani, Fotini

2017-01-01

For the case of approximation of convection-diffusion equations using piecewise affine continuous finite elements a new edge-based nonlinear diffusion operator is proposed that makes the scheme satisfy a discrete maximum principle. The diffusion operator is shown to be Lipschitz continuous and linearity preserving. Using these properties we provide a full stability and error analysis, which, in the diffusion dominated regime, shows existence, uniqueness and optimal convergence. Then the algebraic flux correction method is recalled and we show that the present method can be interpreted as an algebraic flux correction method for a particular definition of the flux limiters. The performance of the method is illustrated on some numerical test cases in two space dimensions.

Scoring in genetically modified organism proficiency tests based on log-transformed results.

PubMed

Thompson, Michael; Ellison, Stephen L R; Owen, Linda; Mathieson, Kenneth; Powell, Joanne; Key, Pauline; Wood, Roger; Damant, Andrew P

2006-01-01

The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distributions that are sufficiently close to normal to justify interpretation on the basis of the normal distribution.

Error Rates in Measuring Teacher and School Performance Based on Student Test Score Gains. NCEE 2010-4004

ERIC Educational Resources Information Center

Schochet, Peter Z.; Chiang, Hanley S.

2010-01-01

This paper addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using realistic performance measurement system schemes based on hypothesis testing, we develop error rate formulas based on OLS and Empirical Bayes estimators.…

Prescribed performance distributed consensus control for nonlinear multi-agent systems with unknown dead-zone input

NASA Astrophysics Data System (ADS)

Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang

2018-05-01

In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

PubMed Central

2011-01-01

Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices. PMID:21771321

A Comparative Study of Mindfulness Efficiency Based on Islamic-Spiritual Schemes and Group Cognitive Behavioral Therapy on Reduction of Anxiety and Depression in Pregnant Women.

PubMed

Aslami, Elahe; Alipour, Ahmad; Najib, Fatemeh Sadat; Aghayosefi, Alireza

2017-04-01

Anxiety and depression during the pregnancy period are among the factors affecting the pregnancy undesirable outcomes and delivery. One way of controlling anxiety and depression is mindfulness and cognitive behavioral therapy. The purpose of this study was to compare the efficiency of mindfulness based on the Islamic-spiritual schemas and group cognitive behavioral therapy on reduction of anxiety and depression in pregnant women. The research design was semi-experimental in the form of pretest-posttest using a control group. Among the pregnant women in the 16th to 32nd weeks of pregnancy who referred to the health center, 30 pregnant women with high anxiety level and 30 pregnant women with high depression participated in the research. Randomly 15 participants with high depression and 15 participants with high anxiety were considered in the intervention group under the treatment of mindfulness based on Islamic-spiritual schemes. In addition, 15 participants with high scores regarding depression and 15 with high scores in anxiety were considered in the other group. .The control group consisted of 15 pregnant women with high anxiety and depression. Beck anxiety-depression questionnaire was used in two steps of pre-test and post-test. Data were analyzed using SPSS, version 20, and P≤0.05 was considered as significant. The results of multivariate analysis of variance test and tracking Tokey test showed that there was a significant difference between the mean scores of anxiety and depression in the two groups of mindfulness based on spiritual- Islamic scheme (P<0.001) and the group of cognitive behavioral therapy with each other (P<0.001) and with the control group(P<0.001). The mean of anxiety and depression scores decreased in the intervention group, but it increased in the control group. Both therapy methods were effective in reduction of anxiety and depression of pregnant women, but the effect of mindfulness based on spiritual- Islamic schemes was more.

S-Boxes Based on Affine Mapping and Orbit of Power Function

NASA Astrophysics Data System (ADS)

Khan, Mubashar; Azam, Naveed Ahmed

2015-06-01

The demand of data security against computational attacks such as algebraic, differential, linear and interpolation attacks has been increased as a result of rapid advancement in the field of computation. It is, therefore, necessary to develop such cryptosystems which can resist current cryptanalysis and more computational attacks in future. In this paper, we present a multiple S-boxes scheme based on affine mapping and orbit of the power function used in Advanced Encryption Standard (AES). The proposed technique results in 256 different S-boxes named as orbital S-boxes. Rigorous tests and comparisons are performed to analyse the cryptographic strength of each of the orbital S-boxes. Furthermore, gray scale images are encrypted by using multiple orbital S-boxes. Results and simulations show that the encryption strength of the orbital S-boxes against computational attacks is better than that of the existing S-boxes.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

A novel method to estimate the affinity of HLA-A∗0201 restricted CTL epitope

NASA Astrophysics Data System (ADS)

Xu, Yun-sheng; Lin, Yong; Zhu, Bo; Lin, Zhi-hua

2009-02-01

A set of 70 peptides with affinity for the class I MHC HLA-A∗0201 molecule was subjected to quantitative structure-affinity relationship studies based on the SCORE function with good results ( r2 = 0.6982, RMS = 0.280). Then the 'leave-one-out' cross-validation (LOO-CV) and an outer test set including 18 outer samples were used to validate the QSAR model. The results of the LOO-CV were q2 = 0.6188, RMS = 0.315, and the results of outer test set were r2 = 0.5633, RMS = 0.2292. All these show that the QSAR model has good predictability. Statistical analysis showed that the hydrophobic and hydrogen bond interaction played a significant role in peptide-MHC molecule binding. The study also provided useful information for structure modification of CTL epitope, and laid theoretical base for molecular design of therapeutic vaccine.

Enriching peptide libraries for binding affinity and specificity through computationally directed library design

PubMed Central

Foight, Glenna Wink; Chen, T. Scott; Richman, Daniel; Keating, Amy E.

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model. PMID:28236241

Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.

PubMed

Foight, Glenna Wink; Chen, T Scott; Richman, Daniel; Keating, Amy E

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.

Quantum-Mechanics Methodologies in Drug Discovery: Applications of Docking and Scoring in Lead Optimization.

PubMed

Crespo, Alejandro; Rodriguez-Granillo, Agustina; Lim, Victoria T

2017-01-01

The development and application of quantum mechanics (QM) methodologies in computer- aided drug design have flourished in the last 10 years. Despite the natural advantage of QM methods to predict binding affinities with a higher level of theory than those methods based on molecular mechanics (MM), there are only a few examples where diverse sets of protein-ligand targets have been evaluated simultaneously. In this work, we review recent advances in QM docking and scoring for those cases in which a systematic analysis has been performed. In addition, we introduce and validate a simplified QM/MM expression to compute protein-ligand binding energies. Overall, QMbased scoring functions are generally better to predict ligand affinities than those based on classical mechanics. However, the agreement between experimental activities and calculated binding energies is highly dependent on the specific chemical series considered. The advantage of more accurate QM methods is evident in cases where charge transfer and polarization effects are important, for example when metals are involved in the binding process or when dispersion forces play a significant role as in the case of hydrophobic or stacking interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Reliable and Valid Weighted Scoring Instrument for Use in Grading APA-Style Empirical Research Report

ERIC Educational Resources Information Center

Greenberg, Kathleen Puglisi

2012-01-01

The scoring instrument described in this article is based on a deconstruction of the seven sections of an American Psychological Association (APA)-style empirical research report into a set of learning outcomes divided into content-, expression-, and format-related categories. A double-weighting scheme used to score the report yields a final grade…

A recursive field-normalized bibliometric performance indicator: an application to the field of library and information science.

PubMed

Waltman, Ludo; Yan, Erjia; van Eck, Nees Jan

2011-10-01

Two commonly used ideas in the development of citation-based research performance indicators are the idea of normalizing citation counts based on a field classification scheme and the idea of recursive citation weighing (like in PageRank-inspired indicators). We combine these two ideas in a single indicator, referred to as the recursive mean normalized citation score indicator, and we study the validity of this indicator. Our empirical analysis shows that the proposed indicator is highly sensitive to the field classification scheme that is used. The indicator also has a strong tendency to reinforce biases caused by the classification scheme. Based on these observations, we advise against the use of indicators in which the idea of normalization based on a field classification scheme and the idea of recursive citation weighing are combined.

QualComp: a new lossy compressor for quality scores based on rate distortion theory

PubMed Central

2013-01-01

Background Next Generation Sequencing technologies have revolutionized many fields in biology by reducing the time and cost required for sequencing. As a result, large amounts of sequencing data are being generated. A typical sequencing data file may occupy tens or even hundreds of gigabytes of disk space, prohibitively large for many users. This data consists of both the nucleotide sequences and per-base quality scores that indicate the level of confidence in the readout of these sequences. Quality scores account for about half of the required disk space in the commonly used FASTQ format (before compression), and therefore the compression of the quality scores can significantly reduce storage requirements and speed up analysis and transmission of sequencing data. Results In this paper, we present a new scheme for the lossy compression of the quality scores, to address the problem of storage. Our framework allows the user to specify the rate (bits per quality score) prior to compression, independent of the data to be compressed. Our algorithm can work at any rate, unlike other lossy compression algorithms. We envisage our algorithm as being part of a more general compression scheme that works with the entire FASTQ file. Numerical experiments show that we can achieve a better mean squared error (MSE) for small rates (bits per quality score) than other lossy compression schemes. For the organism PhiX, whose assembled genome is known and assumed to be correct, we show that it is possible to achieve a significant reduction in size with little compromise in performance on downstream applications (e.g., alignment). Conclusions QualComp is an open source software package, written in C and freely available for download at https://sourceforge.net/projects/qualcomp. PMID:23758828

Evaluation of respiratory and cardiac motion correction schemes in dual gated PET/CT cardiac imaging.

PubMed

Lamare, F; Le Maitre, A; Dawood, M; Schäfers, K P; Fernandez, P; Rimoldi, O E; Visvikis, D

2014-07-01

Cardiac imaging suffers from both respiratory and cardiac motion. One of the proposed solutions involves double gated acquisitions. Although such an approach may lead to both respiratory and cardiac motion compensation there are issues associated with (a) the combination of data from cardiac and respiratory motion bins, and (b) poor statistical quality images as a result of using only part of the acquired data. The main objective of this work was to evaluate different schemes of combining binned data in order to identify the best strategy to reconstruct motion free cardiac images from dual gated positron emission tomography (PET) acquisitions. A digital phantom study as well as seven human studies were used in this evaluation. PET data were acquired in list mode (LM). A real-time position management system and an electrocardiogram device were used to provide the respiratory and cardiac motion triggers registered within the LM file. Acquired data were subsequently binned considering four and six cardiac gates, or the diastole only in combination with eight respiratory amplitude gates. PET images were corrected for attenuation, but no randoms nor scatter corrections were included. Reconstructed images from each of the bins considered above were subsequently used in combination with an affine or an elastic registration algorithm to derive transformation parameters allowing the combination of all acquired data in a particular position in the cardiac and respiratory cycles. Images were assessed in terms of signal-to-noise ratio (SNR), contrast, image profile, coefficient-of-variation (COV), and relative difference of the recovered activity concentration. Regardless of the considered motion compensation strategy, the nonrigid motion model performed better than the affine model, leading to higher SNR and contrast combined with a lower COV. Nevertheless, when compensating for respiration only, no statistically significant differences were observed in the performance of the two motion models considered. Superior image SNR and contrast were seen using the affine respiratory motion model in combination with the diastole cardiac bin in comparison to the use of the whole cardiac cycle. In contrast, when simultaneously correcting for cardiac beating and respiration, the elastic respiratory motion model outperformed the affine model. In this context, four cardiac bins associated with eight respiratory amplitude bins seemed to be adequate. Considering the compensation of respiratory motion effects only, both affine and elastic based approaches led to an accurate resizing and positioning of the myocardium. The use of the diastolic phase combined with an affine model based respiratory motion correction may therefore be a simple approach leading to significant quality improvements in cardiac PET imaging. However, the best performance was obtained with the combined correction for both cardiac and respiratory movements considering all the dual-gated bins independently through the use of an elastic model based motion compensation.

Finite spaces and schemes

NASA Astrophysics Data System (ADS)

Sancho de Salas, Fernando

2017-12-01

A ringed finite space is a ringed space whose underlying topological space is finite. The category of ringed finite spaces contains, fully faithfully, the category of finite topological spaces and the category of affine schemes. Any ringed space, endowed with a finite open covering, produces a ringed finite space. We introduce the notions of schematic finite space and schematic morphism, showing that they behave, with respect to quasi-coherence, like schemes and morphisms of schemes do. Finally, we construct a fully faithful and essentially surjective functor from a localization of a full subcategory of the category of schematic finite spaces and schematic morphisms to the category of quasi-compact and quasi-separated schemes.

Adaptive nearly optimal control for a class of continuous-time nonaffine nonlinear systems with inequality constraints.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2017-01-01

The state inequality constraints have been hardly considered in the literature on solving the nonlinear optimal control problem based the adaptive dynamic programming (ADP) method. In this paper, an actor-critic (AC) algorithm is developed to solve the optimal control problem with a discounted cost function for a class of state-constrained nonaffine nonlinear systems. To overcome the difficulties resulting from the inequality constraints and the nonaffine nonlinearities of the controlled systems, a novel transformation technique with redesigned slack functions and a pre-compensator method are introduced to convert the constrained optimal control problem into an unconstrained one for affine nonlinear systems. Then, based on the policy iteration (PI) algorithm, an online AC scheme is proposed to learn the nearly optimal control policy for the obtained affine nonlinear dynamics. Using the information of the nonlinear model, novel adaptive update laws are designed to guarantee the convergence of the neural network (NN) weights and the stability of the affine nonlinear dynamics without the requirement for the probing signal. Finally, the effectiveness of the proposed method is validated by simulation studies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Influence of various force fields in estimating the binding affinity of acetylcholinesterase inhibitors using fast pulling of ligand scheme

NASA Astrophysics Data System (ADS)

Tam, Nguyen Minh; Vu, Khanh B.; Vu, Van V.; Ngo, Son Tung

2018-06-01

Acetylcholinesterase (AChE) is considered as one of the most favored drug targets for Alzheimer's disease. The effects of different force fields (FFs) on ranking affinity of acetylcholinesterase inhibitors were obtained using the fast pulling of ligand (FPL) method in steered-molecular dynamics (SMD) simulations. GROMOS, AMBER, CHARMM, and OPLS-AA FFs were investigated in this work. The pulling work derived with GROMOS FF has the strongest correlation and smallest error compared with experimental binding affinity. Moreover, the CPU consumption in the calculations using GROMOS FF is the lowest, which could allow us to rank affinity of a large number of AChE ligands.

Comparison of Electrochemical Immunosensors and Aptasensors for Detection of Small Organic Molecules in Environment, Food Safety, Clinical and Public Security.

PubMed

Piro, Benoit; Shi, Shihui; Reisberg, Steeve; Noël, Vincent; Anquetin, Guillaume

2016-02-29

We review here the most frequently reported targets among the electrochemical immunosensors and aptasensors: antibiotics, bisphenol A, cocaine, ochratoxin A and estradiol. In each case, the immobilization procedures are described as well as the transduction schemes and the limits of detection. It is shown that limits of detections are generally two to three orders of magnitude lower for immunosensors than for aptasensors, due to the highest affinities of antibodies. No significant progresses have been made to improve these affinities, but transduction schemes were improved instead, which lead to a regular improvement of the limit of detections corresponding to ca. five orders of magnitude over these last 10 years. These progresses depend on the target, however.

Affinity purification–mass spectrometry and network analysis to understand protein-protein interactions

PubMed Central

Morris, John H; Knudsen, Giselle M; Verschueren, Erik; Johnson, Jeffrey R; Cimermancic, Peter; Greninger, Alexander L; Pico, Alexander R

2015-01-01

By determining protein-protein interactions in normal, diseased and infected cells, we can improve our understanding of cellular systems and their reaction to various perturbations. In this protocol, we discuss how to use data obtained in affinity purification–mass spectrometry (AP-MS) experiments to generate meaningful interaction networks and effective figures. We begin with an overview of common epitope tagging, expression and AP practices, followed by liquid chromatography–MS (LC-MS) data collection. We then provide a detailed procedure covering a pipeline approach to (i) pre-processing the data by filtering against contaminant lists such as the Contaminant Repository for Affinity Purification (CRAPome) and normalization using the spectral index (SIN) or normalized spectral abundance factor (NSAF); (ii) scoring via methods such as MiST, SAInt and CompPASS; and (iii) testing the resulting scores. Data formats familiar to MS practitioners are then transformed to those most useful for network-based analyses. The protocol also explores methods available in Cytoscape to visualize and analyze these types of interaction data. The scoring pipeline can take anywhere from 1 d to 1 week, depending on one’s familiarity with the tools and data peculiarities. Similarly, the network analysis and visualization protocol in Cytoscape takes 2–4 h to complete with the provided sample data, but we recommend taking days or even weeks to explore one’s data and find the right questions. PMID:25275790

D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies

NASA Astrophysics Data System (ADS)

Gaieb, Zied; Liu, Shuai; Gathiaka, Symon; Chiu, Michael; Yang, Huanwang; Shao, Chenghua; Feher, Victoria A.; Walters, W. Patrick; Kuhn, Bernd; Rudolph, Markus G.; Burley, Stephen K.; Gilson, Michael K.; Amaro, Rommie E.

2018-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.

Landmark-based elastic registration using approximating thin-plate splines.

PubMed

Rohr, K; Stiehl, H S; Sprengel, R; Buzug, T M; Weese, J; Kuhn, M H

2001-06-01

We consider elastic image registration based on a set of corresponding anatomical point landmarks and approximating thin-plate splines. This approach is an extension of the original interpolating thin-plate spline approach and allows to take into account landmark localization errors. The extension is important for clinical applications since landmark extraction is always prone to error. Our approach is based on a minimizing functional and can cope with isotropic as well as anisotropic landmark errors. In particular, in the latter case it is possible to include different types of landmarks, e.g., unique point landmarks as well as arbitrary edge points. Also, the scheme is general with respect to the image dimension and the order of smoothness of the underlying functional. Optimal affine transformations as well as interpolating thin-plate splines are special cases of this scheme. To localize landmarks we use a semi-automatic approach which is based on three-dimensional (3-D) differential operators. Experimental results are presented for two-dimensional as well as 3-D tomographic images of the human brain.

TripSense: A Trust-Based Vehicular Platoon Crowdsensing Scheme with Privacy Preservation in VANETs

PubMed Central

Hu, Hao; Lu, Rongxing; Huang, Cheng; Zhang, Zonghua

2016-01-01

In this paper, we propose a trust-based vehicular platoon crowdsensing scheme, named TripSense, in VANET. The proposed TripSense scheme introduces a trust-based system to evaluate vehicles’ sensing abilities and then selects the more capable vehicles in order to improve sensing results accuracy. In addition, the sensing tasks are accomplished by platoon member vehicles and preprocessed by platoon head vehicles before the data are uploaded to server. Hence, it is less time-consuming and more efficient compared with the way where the data are submitted by individual platoon member vehicles. Hence it is more suitable in ephemeral networks like VANET. Moreover, our proposed TripSense scheme integrates unlinkable pseudo-ID techniques to achieve PM vehicle identity privacy, and employs a privacy-preserving sensing vehicle selection scheme without involving the PM vehicle’s trust score to keep its location privacy. Detailed security analysis shows that our proposed TripSense scheme not only achieves desirable privacy requirements but also resists against attacks launched by adversaries. In addition, extensive simulations are conducted to show the correctness and effectiveness of our proposed scheme. PMID:27258287

Psychological Features and Their Relationship to Movement-Based Subgroups in People Living With Low Back Pain.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Nicholas, Michael K; Hodges, Paul W

2018-01-01

To determine the distribution of higher psychological risk features within movement-based subgroups for people with low back pain (LBP). Cross-sectional observational study. Participants were recruited from physiotherapy clinics and community advertisements. Measures were collected at a university outpatient-based physiotherapy clinic. People (N=102) seeking treatment for LBP. Participants were subgrouped according to 3 classification schemes: Mechanical Diagnosis and Treatment (MDT), Treatment-Based Classification (TBC), and O'Sullivan Classification (OSC). Questionnaires were used to categorize low-, medium-, and high-risk features based on depression, anxiety, and stress (Depression, Anxiety, and Stress Scale-21 Items); fear avoidance (Fear-Avoidance Beliefs Questionnaire); catastrophizing and coping (Pain-Related Self-Symptoms Scale); and self-efficacy (Pain Self-Efficacy Questionnaire). Psychological risk profiles were compared between movement-based subgroups within each scheme. Scores across all questionnaires revealed that most patients had low psychological risk profiles, but there were instances of higher (range, 1%-25%) risk profiles within questionnaire components. The small proportion of individuals with higher psychological risk scores were distributed between subgroups across TBC, MDT, and OSC schemes. Movement-based subgrouping alone cannot inform on individuals with higher psychological risk features. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

PubMed Central

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

2017-01-01

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

LDFT-based watermarking resilient to local desynchronization attacks.

PubMed

Tian, Huawei; Zhao, Yao; Ni, Rongrong; Qin, Lunming; Li, Xuelong

2013-12-01

Up to now, a watermarking scheme that is robust against desynchronization attacks (DAs) is still a grand challenge. Most image watermarking resynchronization schemes in literature can survive individual global DAs (e.g., rotation, scaling, translation, and other affine transforms), but few are resilient to challenging cropping and local DAs. The main reason is that robust features for watermark synchronization are only globally invariable rather than locally invariable. In this paper, we present a blind image watermarking resynchronization scheme against local transform attacks. First, we propose a new feature transform named local daisy feature transform (LDFT), which is not only globally but also locally invariable. Then, the binary space partitioning (BSP) tree is used to partition the geometrically invariant LDFT space. In the BSP tree, the location of each pixel is fixed under global transform, local transform, and cropping. Lastly, the watermarking sequence is embedded bit by bit into each leaf node of the BSP tree by using the logarithmic quantization index modulation watermarking embedding method. Simulation results show that the proposed watermarking scheme can survive numerous kinds of distortions, including common image-processing attacks, local and global DAs, and noninvertible cropping.

A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control.

PubMed

Phung, Dung; Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia

2016-10-01

To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings. © 2016 John Wiley & Sons Ltd.

Continuous, age-related plumage variation in male Kirtland's Warblers

Treesearch

John R. Probst; Deahn M. Donner; Michael A. Bozek

2007-01-01

The ability to age individual birds visually in the field based on plumage variation could provide important demographic and biogeographical information. We describe an approach to infer ages from a distribution of plumage scores of free-ranging male Kirtland's Warblers (Dendroica kinlandii). We assigned ages to males using a scoring scheme (0-...

High affinity ligands from in vitro selection: Complex targets

PubMed Central

Morris, Kevin N.; Jensen, Kirk B.; Julin, Carol M.; Weil, Michael; Gold, Larry

1998-01-01

Human red blood cell membranes were used as a model system to determine if the systematic evolution of ligands by exponential enrichment (SELEX) methodology, an in vitro protocol for isolating high-affinity oligonucleotides that bind specifically to virtually any single protein, could be used with a complex mixture of potential targets. Ligands to multiple targets were generated simultaneously during the selection process, and the binding affinities of these ligands for their targets are comparable to those found in similar experiments against pure targets. A secondary selection scheme, deconvolution-SELEX, facilitates rapid isolation of the ligands to targets of special interest within the mixture. SELEX provides high-affinity compounds for multiple targets in a mixture and might allow a means for dissecting complex biological systems. PMID:9501188

A Comparative Study of Mindfulness Efficiency Based on Islamic-Spiritual Schemes and Group Cognitive Behavioral Therapy on Reduction of Anxiety and Depression in Pregnant Women

PubMed Central

Aslami, Elahe; Alipour, Ahmad; Najib, Fatemeh Sadat; Aghayosefi, Alireza

2017-01-01

ABSTRACT Background: Anxiety and depression during the pregnancy period are among the factors affecting the pregnancy undesirable outcomes and delivery. One way of controlling anxiety and depression is mindfulness and cognitive behavioral therapy. The purpose of this study was to compare the efficiency of mindfulness based on the Islamic-spiritual schemas and group cognitive behavioral therapy on reduction of anxiety and depression in pregnant women. Methods: The research design was semi-experimental in the form of pretest-posttest using a control group. Among the pregnant women in the 16th to 32nd weeks of pregnancy who referred to the health center, 30 pregnant women with high anxiety level and 30 pregnant women with high depression participated in the research. Randomly 15 participants with high depression and 15 participants with high anxiety were considered in the intervention group under the treatment of mindfulness based on Islamic-spiritual schemes. In addition, 15 participants with high scores regarding depression and 15 with high scores in anxiety were considered in the other group. .The control group consisted of 15 pregnant women with high anxiety and depression. Beck anxiety-depression questionnaire was used in two steps of pre-test and post-test. Data were analyzed using SPSS, version 20, and P≤0.05 was considered as significant. Results: The results of multivariate analysis of variance test and tracking Tokey test showed that there was a significant difference between the mean scores of anxiety and depression in the two groups of mindfulness based on spiritual- Islamic scheme (P<0.001) and the group of cognitive behavioral therapy with each other (P<0.001) and with the control group(P<0.001). The mean of anxiety and depression scores decreased in the intervention group, but it increased in the control group. Conclusion: Both therapy methods were effective in reduction of anxiety and depression of pregnant women, but the effect of mindfulness based on spiritual- Islamic schemes was more. PMID:28409168

QUASAR--scoring and ranking of sequence-structure alignments.

PubMed

Birzele, Fabian; Gewehr, Jan E; Zimmer, Ralf

2005-12-15

Sequence-structure alignments are a common means for protein structure prediction in the fields of fold recognition and homology modeling, and there is a broad variety of programs that provide such alignments based on sequence similarity, secondary structure or contact potentials. Nevertheless, finding the best sequence-structure alignment in a pool of alignments remains a difficult problem. QUASAR (quality of sequence-structure alignments ranking) provides a unifying framework for scoring sequence-structure alignments that aids finding well-performing combinations of well-known and custom-made scoring schemes. Those scoring functions can be benchmarked against widely accepted quality scores like MaxSub, TMScore, Touch and APDB, thus enabling users to test their own alignment scores against 'standard-of-truth' structure-based scores. Furthermore, individual score combinations can be optimized with respect to benchmark sets based on known structural relationships using QUASAR's in-built optimization routines.

Comparison of Electrochemical Immunosensors and Aptasensors for Detection of Small Organic Molecules in Environment, Food Safety, Clinical and Public Security

PubMed Central

Piro, Benoit; Shi, Shihui; Reisberg, Steeve; Noël, Vincent; Anquetin, Guillaume

2016-01-01

We review here the most frequently reported targets among the electrochemical immunosensors and aptasensors: antibiotics, bisphenol A, cocaine, ochratoxin A and estradiol. In each case, the immobilization procedures are described as well as the transduction schemes and the limits of detection. It is shown that limits of detections are generally two to three orders of magnitude lower for immunosensors than for aptasensors, due to the highest affinities of antibodies. No significant progresses have been made to improve these affinities, but transduction schemes were improved instead, which lead to a regular improvement of the limit of detections corresponding to ca. five orders of magnitude over these last 10 years. These progresses depend on the target, however. PMID:26938570

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

Phase II evaluation of clinical coding schemes: completeness, taxonomy, mapping, definitions, and clarity. CPRI Work Group on Codes and Structures.

PubMed

Campbell, J R; Carpenter, P; Sneiderman, C; Cohn, S; Chute, C G; Warren, J

1997-01-01

To compare three potential sources of controlled clinical terminology (READ codes version 3.1, SNOMED International, and Unified Medical Language System (UMLS) version 1.6) relative to attributes of completeness, clinical taxonomy, administrative mapping, term definitions and clarity (duplicate coding rate). The authors assembled 1929 source concept records from a variety of clinical information taken from four medical centers across the United States. The source data included medical as well as ample nursing terminology. The source records were coded in each scheme by an investigator and checked by the coding scheme owner. The codings were then scored by an independent panel of clinicians for acceptability. Codes were checked for definitions provided with the scheme. Codes for a random sample of source records were analyzed by an investigator for "parent" and "child" codes within the scheme. Parent and child pairs were scored by an independent panel of medical informatics specialists for clinical acceptability. Administrative and billing code mapping from the published scheme were reviewed for all coded records and analyzed by independent reviewers for accuracy. The investigator for each scheme exhaustively searched a sample of coded records for duplications. SNOMED was judged to be significantly more complete in coding the source material than the other schemes (SNOMED* 70%; READ 57%; UMLS 50%; *p < .00001). SNOMED also had a richer clinical taxonomy judged by the number of acceptable first-degree relatives per coded concept (SNOMED* 4.56, UMLS 3.17; READ 2.14, *p < .005). Only the UMLS provided any definitions; these were found for 49% of records which had a coding assignment. READ and UMLS had better administrative mappings (composite score: READ* 40.6%; UMLS* 36.1%; SNOMED 20.7%, *p < .00001), and SNOMED had substantially more duplications of coding assignments (duplication rate: READ 0%; UMLS 4.2%; SNOMED* 13.9%, *p < .004) associated with a loss of clarity. No major terminology source can lay claim to being the ideal resource for a computer-based patient record. However, based upon this analysis of releases for April 1995, SNOMED International is considerably more complete, has a compositional nature and a richer taxonomy. Is suffers from less clarity, resulting from a lack of syntax and evolutionary changes in its coding scheme. READ has greater clarity and better mapping to administrative schemes (ICD-10 and OPCS-4), is rapidly changing and is less complete. UMLS is a rich lexical resource, with mappings to many source vocabularies. It provides definitions for many of its terms. However, due to the varying granularities and purposes of its source schemes, it has limitations for representation of clinical concepts within a computer-based patient record.

Phase II Evaluation of Clinical Coding Schemes

PubMed Central

Campbell, James R.; Carpenter, Paul; Sneiderman, Charles; Cohn, Simon; Chute, Christopher G.; Warren, Judith

1997-01-01

Abstract Objective: To compare three potential sources of controlled clinical terminology (READ codes version 3.1, SNOMED International, and Unified Medical Language System (UMLS) version 1.6) relative to attributes of completeness, clinical taxonomy, administrative mapping, term definitions and clarity (duplicate coding rate). Methods: The authors assembled 1929 source concept records from a variety of clinical information taken from four medical centers across the United States. The source data included medical as well as ample nursing terminology. The source records were coded in each scheme by an investigator and checked by the coding scheme owner. The codings were then scored by an independent panel of clinicians for acceptability. Codes were checked for definitions provided with the scheme. Codes for a random sample of source records were analyzed by an investigator for “parent” and “child” codes within the scheme. Parent and child pairs were scored by an independent panel of medical informatics specialists for clinical acceptability. Administrative and billing code mapping from the published scheme were reviewed for all coded records and analyzed by independent reviewers for accuracy. The investigator for each scheme exhaustively searched a sample of coded records for duplications. Results: SNOMED was judged to be significantly more complete in coding the source material than the other schemes (SNOMED* 70%; READ 57%; UMLS 50%; *p <.00001). SNOMED also had a richer clinical taxonomy judged by the number of acceptable first-degree relatives per coded concept (SNOMED* 4.56; UMLS 3.17; READ 2.14, *p <.005). Only the UMLS provided any definitions; these were found for 49% of records which had a coding assignment. READ and UMLS had better administrative mappings (composite score: READ* 40.6%; UMLS* 36.1%; SNOMED 20.7%, *p <. 00001), and SNOMED had substantially more duplications of coding assignments (duplication rate: READ 0%; UMLS 4.2%; SNOMED* 13.9%, *p <. 004) associated with a loss of clarity. Conclusion: No major terminology source can lay claim to being the ideal resource for a computer-based patient record. However, based upon this analysis of releases for April 1995, SNOMED International is considerably more complete, has a compositional nature and a richer taxonomy. It suffers from less clarity, resulting from a lack of syntax and evolutionary changes in its coding scheme. READ has greater clarity and better mapping to administrative schemes (ICD-10 and OPCS-4), is rapidly changing and is less complete. UMLS is a rich lexical resource, with mappings to many source vocabularies. It provides definitions for many of its terms. However, due to the varying granularities and purposes of its source schemes, it has limitations for representation of clinical concepts within a computer-based patient record. PMID:9147343

Robust estimation-free prescribed performance back-stepping control of air-breathing hypersonic vehicles without affine models

NASA Astrophysics Data System (ADS)

Bu, Xiangwei; Wu, Xiaoyan; Huang, Jiaqi; Wei, Daozhi

2016-11-01

This paper investigates the design of a novel estimation-free prescribed performance non-affine control strategy for the longitudinal dynamics of an air-breathing hypersonic vehicle (AHV) via back-stepping. The proposed control scheme is capable of guaranteeing tracking errors of velocity, altitude, flight-path angle, pitch angle and pitch rate with prescribed performance. By prescribed performance, we mean that the tracking error is limited to a predefined arbitrarily small residual set, with convergence rate no less than a certain constant, exhibiting maximum overshoot less than a given value. Unlike traditional back-stepping designs, there is no need of an affine model in this paper. Moreover, both the tedious analytic and numerical computations of time derivatives of virtual control laws are completely avoided. In contrast to estimation-based strategies, the presented estimation-free controller possesses much lower computational costs, while successfully eliminating the potential problem of parameter drifting. Owing to its independence on an accurate AHV model, the studied methodology exhibits excellent robustness against system uncertainties. Finally, simulation results from a fully nonlinear model clarify and verify the design.

PANDA: Protein function prediction using domain architecture and affinity propagation.

PubMed

Wang, Zheng; Zhao, Chenguang; Wang, Yiheng; Sun, Zheng; Wang, Nan

2018-02-22

We developed PANDA (Propagation of Affinity and Domain Architecture) to predict protein functions in the format of Gene Ontology (GO) terms. PANDA at first executes profile-profile alignment algorithm to search against PfamA, KOG, COG, and SwissProt databases, and then launches PSI-BLAST against UniProt for homologue search. PANDA integrates a domain architecture inference algorithm based on the Bayesian statistics that calculates the probability of having a GO term. All the candidate GO terms are pooled and filtered based on Z-score. After that, the remaining GO terms are clustered using an affinity propagation algorithm based on the GO directed acyclic graph, followed by a second round of filtering on the clusters of GO terms. We benchmarked the performance of all the baseline predictors PANDA integrates and also for every pooling and filtering step of PANDA. It can be found that PANDA achieves better performances in terms of area under the curve for precision and recall compared to the baseline predictors. PANDA can be accessed from http://dna.cs.miami.edu/PANDA/ .

Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics.

PubMed

Gul, Ahmet; Erman, Burak

2018-01-16

Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.

Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics

NASA Astrophysics Data System (ADS)

Gul, Ahmet; Erman, Burak

2018-03-01

Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.

Proposed new classification scheme for chemical injury to the human eye.

PubMed

Bagley, Daniel M; Casterton, Phillip L; Dressler, William E; Edelhauser, Henry F; Kruszewski, Francis H; McCulley, James P; Nussenblatt, Robert B; Osborne, Rosemarie; Rothenstein, Arthur; Stitzel, Katherine A; Thomas, Karluss; Ward, Sherry L

2006-07-01

Various ocular alkali burn classification schemes have been published and used to grade human chemical eye injuries for the purpose of identifying treatments and forecasting outcomes. The ILSI chemical eye injury classification scheme was developed for the additional purpose of collecting detailed human eye injury data to provide information on the mechanisms associated with chemical eye injuries. This information will have clinical application, as well as use in the development and validation of new methods to assess ocular toxicity. A panel of ophthalmic researchers proposed the new classification scheme based upon current knowledge of the mechanisms of eye injury, and their collective clinical and research experience. Additional ophthalmologists and researchers were surveyed to critique the scheme. The draft scheme was revised, and the proposed scheme represents the best consensus from at least 23 physicians and scientists. The new scheme classifies chemical eye injury into five categories based on clinical signs, symptoms, and expected outcomes. Diagnostic classification is based primarily on two clinical endpoints: (1) the extent (area) of injury at the limbus, and (2) the degree of injury (area and depth) to the cornea. The new classification scheme provides a uniform system for scoring eye injury across chemical classes, and provides enough detail for the clinician to collect data that will be relevant to identifying the mechanisms of ocular injury.

Affinity chromatography on monolithic supports for simultaneous and high-throughput isolation of immunoglobulins from human serum.

PubMed

Martinović, Tamara; Andjelković, Uroš; Klobučar, Marko; Černigoj, Urh; Vidič, Jana; Lučić, Marina; Pavelić, Krešimir; Josić, Djuro

2017-11-01

Posttranslational modifications of immunoglobulins have been a topic of great interest and have been repeatedly reported as a major factor in disease pathology. Cost-effective, reproducible, and high-throughput (HTP) isolation of immunoglobulins from human serum is vital for studying the changes in protein structure and the following understanding of disease development. Although there are many methods for the isolation of specific immunoglobulin classes, only a few of them are applicable for isolation of all subtypes and variants. Here, we present the development of a scheme for fast and simultaneous affinity purification of α (A), γ (G), and μ (M) immunoglobulins from human serum through affinity monolith chromatography. Affinity-based monolithic columns with immobilized protein A, G, or L were used for antibody isolation. Monolithic stationary phases have a high surface accessibility of binding sites, large flow-through channels, and can be operated at high flow rates, making them the ideal supports for HTP isolation of biopolymers. The presented method can be used for HTP screening of human serum in order to simultaneously isolate all three above-mentioned immunoglobulins and determine their concentration and changes in their glycosylation pattern as potential prognostic and diagnostic disease biomarkers. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance of stroke risk scores in older people with atrial fibrillation not taking warfarin: comparative cohort study from BAFTA trial.

PubMed

Hobbs, F D R; Roalfe, A K; Lip, G Y H; Fletcher, K; Fitzmaurice, D A; Mant, J

2011-06-23

To compare the predictive power of the main existing and recently proposed schemes for stratification of risk of stroke in older patients with atrial fibrillation. Comparative cohort study of eight risk stratification scores. Trial of thromboprophylaxis in stroke, the Birmingham Atrial Fibrillation in the Aged (BAFTA) trial. 665 patients aged 75 or over with atrial fibrillation based in the community who were randomised to the BAFTA trial and were not taking warfarin throughout or for part of the study period. Events rates of stroke and thromboembolism. 54 (8%) patients had an ischaemic stroke, four (0.6%) had a systemic embolism, and 13 (2%) had a transient ischaemic attack. The distribution of patients classified into the three risk categories (low, moderate, high) was similar across three of the risk stratification scores (revised CHADS(2), NICE, ACC/AHA/ESC), with most patients categorised as high risk (65-69%, n = 460-457) and the remaining classified as moderate risk. The original CHADS(2) (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, previous Stroke) score identified the lowest number as high risk (27%, n = 180). The incremental risk scores of CHADS(2), Rietbrock modified CHADS(2), and CHA(2)DS(2)-VASc (CHA(2)DS(2)-Vascular disease, Age 65-74 years, Sex) failed to show an increase in risk at the upper range of scores. The predictive accuracy was similar across the tested schemes with C statistic ranging from 0.55 (original CHADS(2)) to 0.62 (Rietbrock modified CHADS(2)), with all except the original CHADS(2) predicting better than chance. Bootstrapped paired comparisons provided no evidence of significant differences between the discriminatory ability of the schemes. Based on this single trial population, current risk stratification schemes in older people with atrial fibrillation have only limited ability to predict the risk of stroke. Given the systematic undertreatment of older people with anticoagulation, and the relative safety of warfarin versus aspirin in those aged over 70, there could be a pragmatic rationale for classifying all patients over 75 as "high risk" until better tools are available.

Evaluation of respiratory and cardiac motion correction schemes in dual gated PET/CT cardiac imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamare, F., E-mail: frederic.lamare@chu-bordeaux.fr; Fernandez, P.; CNRS, INCIA, UMR 5287, F-33400 Talence

Purpose: Cardiac imaging suffers from both respiratory and cardiac motion. One of the proposed solutions involves double gated acquisitions. Although such an approach may lead to both respiratory and cardiac motion compensation there are issues associated with (a) the combination of data from cardiac and respiratory motion bins, and (b) poor statistical quality images as a result of using only part of the acquired data. The main objective of this work was to evaluate different schemes of combining binned data in order to identify the best strategy to reconstruct motion free cardiac images from dual gated positron emission tomography (PET)more » acquisitions. Methods: A digital phantom study as well as seven human studies were used in this evaluation. PET data were acquired in list mode (LM). A real-time position management system and an electrocardiogram device were used to provide the respiratory and cardiac motion triggers registered within the LM file. Acquired data were subsequently binned considering four and six cardiac gates, or the diastole only in combination with eight respiratory amplitude gates. PET images were corrected for attenuation, but no randoms nor scatter corrections were included. Reconstructed images from each of the bins considered above were subsequently used in combination with an affine or an elastic registration algorithm to derive transformation parameters allowing the combination of all acquired data in a particular position in the cardiac and respiratory cycles. Images were assessed in terms of signal-to-noise ratio (SNR), contrast, image profile, coefficient-of-variation (COV), and relative difference of the recovered activity concentration. Results: Regardless of the considered motion compensation strategy, the nonrigid motion model performed better than the affine model, leading to higher SNR and contrast combined with a lower COV. Nevertheless, when compensating for respiration only, no statistically significant differences were observed in the performance of the two motion models considered. Superior image SNR and contrast were seen using the affine respiratory motion model in combination with the diastole cardiac bin in comparison to the use of the whole cardiac cycle. In contrast, when simultaneously correcting for cardiac beating and respiration, the elastic respiratory motion model outperformed the affine model. In this context, four cardiac bins associated with eight respiratory amplitude bins seemed to be adequate. Conclusions: Considering the compensation of respiratory motion effects only, both affine and elastic based approaches led to an accurate resizing and positioning of the myocardium. The use of the diastolic phase combined with an affine model based respiratory motion correction may therefore be a simple approach leading to significant quality improvements in cardiac PET imaging. However, the best performance was obtained with the combined correction for both cardiac and respiratory movements considering all the dual-gated bins independently through the use of an elastic model based motion compensation.« less

Molecular insight of isotypes specific β-tubulin interaction of tubulin heterodimer with noscapinoids

NASA Astrophysics Data System (ADS)

Santoshi, Seneha; Naik, Pradeep K.

2014-07-01

Noscapine and its derivatives bind stoichiometrically to tubulin, alter its dynamic instability and thus effectively inhibit the cellular proliferation of a wide variety of cancer cells including many drug-resistant variants. The tubulin molecule is composed of α- and β-tubulin, which exist as various isotypes whose distribution and drug-binding properties are significantly different. Although the noscapinoids bind to a site overlapping with colchicine, their interaction is more biased towards β-tubulin. In fact, their precise interaction and binding affinity with specific isotypes of β-tubulin in the αβ-heterodimer has never been addressed. In this study, the binding affinity of a panel of noscapinoids with each type of tubulin was investigated computationally. We found that the binding score of a specific noscapinoid with each type of tubulin isotype is different. Specifically, amino-noscapine has the highest binding score of -6.4, -7.2, -7.4 and -7.3 kcal/mol with αβI, αβII, αβIII and αβIV isotypes, respectively. Similarly 10 showed higher binding affinity of -6.8 kcal/mol with αβV, whereas 8 had the highest binding affinity of -7.2, -7.1 and -7.2 kcal/mol, respectively with αβVI, αβVII and αβVIII isotypes. More importantly, both amino-noscapine and its clinical derivative, bromo-noscapine have the highest binding affinity of -46.2 and -38.1 kcal/mol against αβIII (overexpression of αβIII has been associated with resistance to a wide range of chemotherapeutic drugs for several human malignancies) as measured using MM-PBSA. Knowledge of the isotype specificity of the noscapinoids may allow for development of novel therapeutic agents based on this class of drugs.

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.

PubMed

Ballester, Pedro J; Mitchell, John B O

2010-05-01

Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that characterize the complex, which also include parameters fitted to experimental or simulation data and its predicted binding affinity. The inherent problem of this rigid approach is that it leads to poor predictivity for those complexes that do not conform to the modelling assumptions. Moreover, resampling strategies, such as cross-validation or bootstrapping, are still not systematically used to guard against the overfitting of calibration data in parameter estimation for scoring functions. We propose a novel scoring function (RF-Score) that circumvents the need for problematic modelling assumptions via non-parametric machine learning. In particular, Random Forest was used to implicitly capture binding effects that are hard to model explicitly. RF-Score is compared with the state of the art on the demanding PDBbind benchmark. Results show that RF-Score is a very competitive scoring function. Importantly, RF-Score's performance was shown to improve dramatically with training set size and hence the future availability of more high-quality structural and interaction data is expected to lead to improved versions of RF-Score. pedro.ballester@ebi.ac.uk; jbom@st-andrews.ac.uk Supplementary data are available at Bioinformatics online.

Practical image registration concerns overcome by the weighted and filtered mutual information metric

NASA Astrophysics Data System (ADS)

Keane, Tommy P.; Saber, Eli; Rhody, Harvey; Savakis, Andreas; Raj, Jeffrey

2012-04-01

Contemporary research in automated panorama creation utilizes camera calibration or extensive knowledge of camera locations and relations to each other to achieve successful results. Research in image registration attempts to restrict these same camera parameters or apply complex point-matching schemes to overcome the complications found in real-world scenarios. This paper presents a novel automated panorama creation algorithm by developing an affine transformation search based on maximized mutual information (MMI) for region-based registration. Standard MMI techniques have been limited to applications with airborne/satellite imagery or medical images. We show that a novel MMI algorithm can approximate an accurate registration between views of realistic scenes of varying depth distortion. The proposed algorithm has been developed using stationary, color, surveillance video data for a scenario with no a priori camera-to-camera parameters. This algorithm is robust for strict- and nearly-affine-related scenes, while providing a useful approximation for the overlap regions in scenes related by a projective homography or a more complex transformation, allowing for a set of efficient and accurate initial conditions for pixel-based registration.

Clinical risk scoring for predicting non-alcoholic fatty liver disease in metabolic syndrome patients (NAFLD-MS score).

PubMed

Saokaew, Surasak; Kanchanasuwan, Shada; Apisarnthanarak, Piyaporn; Charoensak, Aphinya; Charatcharoenwitthaya, Phunchai; Phisalprapa, Pochamana; Chaiyakunapruk, Nathorn

2017-10-01

Non-alcoholic fatty liver disease (NAFLD) can progress from simple steatosis to hepatocellular carcinoma. None of tools have been developed specifically for high-risk patients. This study aimed to develop a simple risk scoring to predict NAFLD in patients with metabolic syndrome (MetS). A total of 509 patients with MetS were recruited. All were diagnosed by clinicians with ultrasonography-confirmed whether they were patients with NAFLD. Patients were randomly divided into derivation (n=400) and validation (n=109) cohort. To develop the risk score, clinical risk indicators measured at the time of recruitment were built by logistic regression. Regression coefficients were transformed into item scores and added up to a total score. A risk scoring scheme was developed from clinical predictors: BMI ≥25, AST/ALT ≥1, ALT ≥40, type 2 diabetes mellitus and central obesity. The scoring scheme was applied in validation cohort to test the performance. The scheme explained, by area under the receiver operating characteristic curve (AuROC), 76.8% of being NAFLD with good calibration (Hosmer-Lemeshow χ 2 =4.35; P=.629). The positive likelihood ratio of NAFLD in patients with low risk (scores below 3) and high risk (scores 5 and over) were 2.32 (95% CI: 1.90-2.82) and 7.77 (95% CI: 2.47-24.47) respectively. When applied in validation cohort, the score showed good performance with AuROC 76.7%, and illustrated 84%, and 100% certainty in low- and high-risk groups respectively. A simple and non-invasive scoring scheme of five predictors provides good prediction indices for NAFLD in MetS patients. This scheme may help clinicians in order to take further appropriate action. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identification of a ligand for tumor necrosis factor receptor from Chinese herbs by combination of surface plasmon resonance biosensor and UPLC-MS.

PubMed

Cao, Yan; Li, Ying-Hua; Lv, Di-Ya; Chen, Xiao-Fei; Chen, Lang-Dong; Zhu, Zhen-Yu; Chai, Yi-Feng; Zhang, Jun-Ping

2016-07-01

Identification of bioactive compounds directly from complex herbal extracts is a key issue in the study of Chinese herbs. The present study describes the establishment and application of a sensitive, efficient, and convenient method based on surface plasmon resonance (SPR) biosensors for screening active ingredients targeting tumor necrosis factor receptor type 1 (TNF-R1) from Chinese herbs. Concentration-adjusted herbal extracts were subjected to SPR binding assay, and a remarkable response signal was observed in Rheum officinale extract. Then, the TNF-R1-bound ingredients were recovered, enriched, and analyzed by UPLC-QTOF/MS. As a result, physcion-8-O-β-D-monoglucoside (PMG) was identified as a bioactive compound, and the affinity constant of PMG to TNF-R1 was determined by SPR affinity analysis (K D  = 376 nM). Pharmacological assays revealed that PMG inhibited TNF-α-induced cytotoxicity and apoptosis in L929 cells via TNF-R1. Although PMG was a trace component in the chemical constituents of the R. officinale extract, it had considerable anti-inflammatory activities. It was found for the first time that PMG was a ligand for TNF receptor from herbal medicines. The proposed SPR-based screening method may prove to be an effective solution to analyzing bioactive components of Chinese herbs and other complex drug systems. Graphical abstract Scheme of the method based on SPR biosensor for screening and recovering active ingredients from complex herbal extracts and UPLC-MS for identifying them. Scheme of the method based on SPR biosensor for screening and recovering active ingredients from complex herbal extracts and UPLC-MS for identifying them.

A novel evaluation method for building construction project based on integrated information entropy with reliability theory.

PubMed

Bai, Xiao-ping; Zhang, Xi-wei

2013-01-01

Selecting construction schemes of the building engineering project is a complex multiobjective optimization decision process, in which many indexes need to be selected to find the optimum scheme. Aiming at this problem, this paper selects cost, progress, quality, and safety as the four first-order evaluation indexes, uses the quantitative method for the cost index, uses integrated qualitative and quantitative methodologies for progress, quality, and safety indexes, and integrates engineering economics, reliability theories, and information entropy theory to present a new evaluation method for building construction project. Combined with a practical case, this paper also presents detailed computing processes and steps, including selecting all order indexes, establishing the index matrix, computing score values of all order indexes, computing the synthesis score, sorting all selected schemes, and making analysis and decision. Presented method can offer valuable references for risk computing of building construction projects.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

PubMed

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

PubMed

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

2017-01-09

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computational redesign of a protein-protein interface for high affinity and binding specificity using modular architecture and naturally occurring template fragments.

PubMed

Potapov, V; Reichmann, D; Abramovich, R; Filchtinski, D; Zohar, N; Ben Halevy, D; Edelman, M; Sobolev, V; Schreiber, G

2008-12-05

A new method is presented for the redesign of protein-protein interfaces, resulting in specificity of the designed pair while maintaining high affinity. The design is based on modular interface architecture and was carried out on the interaction between TEM1 beta-lactamase and its inhibitor protein, beta-lactamase inhibitor protein. The interface between these two proteins is composed of several mostly independent modules. We previously showed that it is possible to delete a complete module without affecting the overall structure of the interface. Here, we replace a complete module with structure fragments taken from nonrelated proteins. Nature-optimized fragments were chosen from 10(7) starting templates found in the Protein Data Bank. A procedure was then developed to identify sets of interacting template residues with a backbone arrangement mimicking the original module. This generated a final list of 361 putative replacement modules that were ranked using a novel scoring function based on grouped atom-atom contact surface areas. The top-ranked designed complex exhibited an affinity of at least the wild-type level and a mode of binding that was remarkably specific despite the absence of negative design in the procedure. In retrospect, the combined application of three factors led to the success of the design approach: utilizing the modular construction of the interface, capitalizing on native rather than artificial templates, and ranking with an accurate atom-atom contact surface scoring function.

Automated scoring system of standard uptake value for torso FDG-PET images

NASA Astrophysics Data System (ADS)

Hara, Takeshi; Kobayashi, Tatsunori; Kawai, Kazunao; Zhou, Xiangrong; Itoh, Satoshi; Katafuchi, Tetsuro; Fujita, Hiroshi

2008-03-01

The purpose of this work was to develop an automated method to calculate the score of SUV for torso region on FDG-PET scans. The three dimensional distributions for the mean and the standard deviation values of SUV were stored in each volume to score the SUV in corresponding pixel position within unknown scans. The modeling methods is based on SPM approach using correction technique of Euler characteristic and Resel (Resolution element). We employed 197 nor-mal cases (male: 143, female: 54) to assemble the normal metabolism distribution of FDG. The physique were registered each other in a rectangular parallelepiped shape using affine transformation and Thin-Plate-Spline technique. The regions of the three organs were determined based on semi-automated procedure. Seventy-three abnormal spots were used to estimate the effectiveness of the scoring methods. As a result, the score images correctly represented that the scores for normal cases were between zeros to plus/minus 2 SD. Most of the scores of abnormal spots associated with cancer were lager than the upper of the SUV interval of normal organs.

Partial and total actuator faults accommodation for input-affine nonlinear process plants.

PubMed

Mihankhah, Amin; Salmasi, Farzad R; Salahshoor, Karim

2013-05-01

In this paper, a new fault-tolerant control system is proposed for input-affine nonlinear plants based on Model Reference Adaptive System (MRAS) structure. The proposed method has the capability to accommodate both partial and total actuator failures along with bounded external disturbances. In this methodology, the conventional MRAS control law is modified by augmenting two compensating terms. One of these terms is added to eliminate the nonlinear dynamic, while the other is reinforced to compensate the distractive effects of the total actuator faults and external disturbances. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed method. Moreover, the control structure has good robustness capability against the parameter variation. The performance of this scheme is evaluated using a CSTR system and the results were satisfactory. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

How Is Emergent Writing Based on Drawing? Analyses of Children's Products and Their Sorting by Children and Mothers.

ERIC Educational Resources Information Center

Levin, Iris; Bus, Adriana G.

2003-01-01

Compared 28- to 53-month-olds' writing and drawing. Scores on a writing scale composed of graphic, "writing-like," and symbolic schemes improved with age. Recognition of drawings as drawings preceded recognition of writings as writings. Writing and drawing scores were substantially correlated, even with age partialed out, suggesting that…

GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

NASA Astrophysics Data System (ADS)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.

Mobile Technology Affinity in Renal Transplant Recipients.

PubMed

Reber, S; Scheel, J; Stoessel, L; Schieber, K; Jank, S; Lüker, C; Vitinius, F; Grundmann, F; Eckardt, K-U; Prokosch, H-U; Erim, Y

Medication nonadherence is a common problem in renal transplant recipients (RTRs). Mobile health approaches to improve medication adherence are a current trend, and several medication adherence apps are available. However, it is unknown whether RTRs use these technologies and to what extent. In the present study, the mobile technology affinity of RTRs was analyzed. We hypothesized significant age differences in mobile technology affinity and that mobile technology affinity is associated with better cognitive functioning as well as higher educational level. A total of 109 RTRs (63% male) participated in the cross-sectional study, with an overall mean age of 51.8 ± 14.2 years. The study included the Technology Experience Questionnaire (TEQ) for the assessment of mobile technology affinity, a cognitive test battery, and sociodemographic data. Overall, 57.4% of the patients used a smartphone or tablet and almost 45% used apps. The TEQ sum score was 20.9 in a possible range from 6 (no affinity to technology) to 30 (very high affinity). Younger patients had significantly higher scores in mobile technology affinity. The only significant gender difference was found in having fun with using electronic devices: Men enjoyed technology more than women did. Mobile technology affinity was positively associated with cognitive functioning and educational level. Young adult patients might profit most from mobile health approaches. Furthermore, high educational level and normal cognitive functioning promote mobile technology affinity. This should be kept in mind when designing mobile technology health (mHealth) interventions for RTRs. For beneficial mHealth interventions, further research on potential barriers and desired technologic features is necessary to adapt apps to patients' needs. Copyright © 2017 Elsevier Inc. All rights reserved.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Support vector regression scoring of receptor-ligand complexes for rank-ordering and virtual screening of chemical libraries.

PubMed

Li, Liwei; Wang, Bo; Meroueh, Samy O

2011-09-26

The community structure-activity resource (CSAR) data sets are used to develop and test a support vector machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR data sets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physicochemical properties. SVR-KB and SVR-EP were compared to seven other widely used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock, and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind data set outperformed all other scoring functions, including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman, and Kendall. It was interesting that higher performance in rank ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed a much higher enrichment, outperforming all other scoring functions tested, and was comparable in performance to our previously derived scoring function SVM-SP.

Cut-Off Points for Mild, Moderate, and Severe Pain on the Numeric Rating Scale for Pain in Patients with Chronic Musculoskeletal Pain: Variability and Influence of Sex and Catastrophizing.

PubMed

Boonstra, Anne M; Stewart, Roy E; Köke, Albère J A; Oosterwijk, René F A; Swaan, Jeannette L; Schreurs, Karlein M G; Schiphorst Preuper, Henrica R

2016-01-01

Objectives: The 0-10 Numeric Rating Scale (NRS) is often used in pain management. The aims of our study were to determine the cut-off points for mild, moderate, and severe pain in terms of pain-related interference with functioning in patients with chronic musculoskeletal pain, to measure the variability of the optimal cut-off points, and to determine the influence of patients' catastrophizing and their sex on these cut-off points. Methods: 2854 patients were included. Pain was assessed by the NRS, functioning by the Pain Disability Index (PDI) and catastrophizing by the Pain Catastrophizing Scale (PCS). Cut-off point schemes were tested using ANOVAs with and without using the PSC scores or sex as co-variates and with the interaction between CP scheme and PCS score and sex, respectively. The variability of the optimal cut-off point schemes was quantified using bootstrapping procedure. Results and conclusion: The study showed that NRS scores ≤ 5 correspond to mild, scores of 6-7 to moderate and scores ≥8 to severe pain in terms of pain-related interference with functioning. Bootstrapping analysis identified this optimal NRS cut-off point scheme in 90% of the bootstrapping samples. The interpretation of the NRS is independent of sex, but seems to depend on catastrophizing. In patients with high catastrophizing tendency, the optimal cut-off point scheme equals that for the total study sample, but in patients with a low catastrophizing tendency, NRS scores ≤ 3 correspond to mild, scores of 4-6 to moderate and scores ≥7 to severe pain in terms of interference with functioning. In these optimal cut-off schemes, NRS scores of 4 and 5 correspond to moderate interference with functioning for patients with low catastrophizing tendency and to mild interference for patients with high catastrophizing tendency. Theoretically one would therefore expect that among the patients with NRS scores 4 and 5 there would be a higher average PDI score for those with low catastrophizing than for those with high catastrophizing. However, we found the opposite. The fact that we did not find the same optimal CP scheme in the subgroups with lower and higher catastrophizing tendency may be due to chance variability.

Cut-Off Points for Mild, Moderate, and Severe Pain on the Numeric Rating Scale for Pain in Patients with Chronic Musculoskeletal Pain: Variability and Influence of Sex and Catastrophizing

PubMed Central

Boonstra, Anne M.; Stewart, Roy E.; Köke, Albère J. A.; Oosterwijk, René F. A.; Swaan, Jeannette L.; Schreurs, Karlein M. G.; Schiphorst Preuper, Henrica R.

2016-01-01

Objectives: The 0–10 Numeric Rating Scale (NRS) is often used in pain management. The aims of our study were to determine the cut-off points for mild, moderate, and severe pain in terms of pain-related interference with functioning in patients with chronic musculoskeletal pain, to measure the variability of the optimal cut-off points, and to determine the influence of patients’ catastrophizing and their sex on these cut-off points. Methods: 2854 patients were included. Pain was assessed by the NRS, functioning by the Pain Disability Index (PDI) and catastrophizing by the Pain Catastrophizing Scale (PCS). Cut-off point schemes were tested using ANOVAs with and without using the PSC scores or sex as co-variates and with the interaction between CP scheme and PCS score and sex, respectively. The variability of the optimal cut-off point schemes was quantified using bootstrapping procedure. Results and conclusion: The study showed that NRS scores ≤ 5 correspond to mild, scores of 6–7 to moderate and scores ≥8 to severe pain in terms of pain-related interference with functioning. Bootstrapping analysis identified this optimal NRS cut-off point scheme in 90% of the bootstrapping samples. The interpretation of the NRS is independent of sex, but seems to depend on catastrophizing. In patients with high catastrophizing tendency, the optimal cut-off point scheme equals that for the total study sample, but in patients with a low catastrophizing tendency, NRS scores ≤ 3 correspond to mild, scores of 4–6 to moderate and scores ≥7 to severe pain in terms of interference with functioning. In these optimal cut-off schemes, NRS scores of 4 and 5 correspond to moderate interference with functioning for patients with low catastrophizing tendency and to mild interference for patients with high catastrophizing tendency. Theoretically one would therefore expect that among the patients with NRS scores 4 and 5 there would be a higher average PDI score for those with low catastrophizing than for those with high catastrophizing. However, we found the opposite. The fact that we did not find the same optimal CP scheme in the subgroups with lower and higher catastrophizing tendency may be due to chance variability. PMID:27746750

Binding Affinity prediction with Property Encoded Shape Distribution signatures

PubMed Central

Das, Sourav; Krein, Michael P.

2010-01-01

We report the use of the molecular signatures known as “Property-Encoded Shape Distributions” (PESD) together with standard Support Vector Machine (SVM) techniques to produce validated models that can predict the binding affinity of a large number of protein ligand complexes. This “PESD-SVM” method uses PESD signatures that encode molecular shapes and property distributions on protein and ligand surfaces as features to build SVM models that require no subjective feature selection. A simple protocol was employed for tuning the SVM models during their development, and the results were compared to SFCscore – a regression-based method that was previously shown to perform better than 14 other scoring functions. Although the PESD-SVM method is based on only two surface property maps, the overall results were comparable. For most complexes with a dominant enthalpic contribution to binding (ΔH/-TΔS > 3), a good correlation between true and predicted affinities was observed. Entropy and solvent were not considered in the present approach and further improvement in accuracy would require accounting for these components rigorously. PMID:20095526

Group Additivity in Ligand Binding Affinity: An Alternative Approach to Ligand Efficiency.

PubMed

Reynolds, Charles H; Reynolds, Ryan C

2017-12-26

Group additivity is a concept that has been successfully applied to a variety of thermochemical and kinetic properties. This includes drug discovery, where functional group additivity is often assumed in ligand binding. Ligand efficiency can be recast as a special case of group additivity where ΔG/HA is the group equivalent (HA is the number of non-hydrogen atoms in a ligand). Analysis of a large data set of protein-ligand binding affinities (K i ) for diverse targets shows that in general ligand binding is distinctly nonlinear. It is possible to create a group equivalent scheme for ligand binding, but only in the context of closely related proteins, at least with regard to size. This finding has broad implications for drug design from both experimental and computational points of view. It also offers a path forward for a more general scheme to assess the efficiency of ligand binding.

Direct Measurement of Equilibrium Constants for High-Affinity Hemoglobins

PubMed Central

Kundu, Suman; Premer, Scott A.; Hoy, Julie A.; Trent, James T.; Hargrove, Mark S.

2003-01-01

The biological functions of heme proteins are linked to their rate and affinity constants for ligand binding. Kinetic experiments are commonly used to measure equilibrium constants for traditional hemoglobins comprised of pentacoordinate ligand binding sites and simple bimolecular reaction schemes. However, kinetic methods do not always yield reliable equilibrium constants with more complex hemoglobins for which reaction mechanisms are not clearly understood. Furthermore, even where reaction mechanisms are clearly understood, it is very difficult to directly measure equilibrium constants for oxygen and carbon monoxide binding to high-affinity (KD ≪ 1 μM) hemoglobins. This work presents a method for direct measurement of equilibrium constants for high-affinity hemoglobins that utilizes a competition for ligands between the "target" protein and an array of "scavenger" hemoglobins with known affinities. This method is described for oxygen and carbon monoxide binding to two hexacoordinate hemoglobins: rice nonsymbiotic hemoglobin and Synechocystis hemoglobin. Our results demonstrate that although these proteins have different mechanisms for ligand binding, their affinities for oxygen and carbon monoxide are similar. Their large affinity constants for oxygen, 285 and ∼100 μM−1 respectively, indicate that they are not capable of facilitating oxygen transport. PMID:12770899

Development of risk-based trading farm scoring system to assist with the control of bovine tuberculosis in cattle in England and Wales.

PubMed

Adkin, A; Brouwer, A; Simons, R R L; Smith, R P; Arnold, M E; Broughan, J; Kosmider, R; Downs, S H

2016-01-01

Identifying and ranking cattle herds with a higher risk of being or becoming infected on known risk factors can help target farm biosecurity, surveillance schemes and reduce spread through animal trading. This paper describes a quantitative approach to develop risk scores, based on the probability of infection in a herd with bovine tuberculosis (bTB), to be used in a risk-based trading (RBT) scheme in England and Wales. To produce a practical scoring system the risk factors included need to be simple and quick to understand, sufficiently informative and derived from centralised national databases to enable verification and assess compliance. A logistic regression identified herd history of bTB, local bTB prevalence, herd size and movements of animals onto farms in batches from high risk areas as being significantly associated with the probability of bTB infection on farm. Risk factors were assigned points using the estimated odds ratios to weight them. The farm risk score was defined as the sum of these individual points yielding a range from 1 to 5 and was calculated for each cattle farm that was trading animals in England and Wales at the start of a year. Within 12 months, of those farms tested, 30.3% of score 5 farms had a breakdown (sensitivity). Of farms scoring 1-4 only 5.4% incurred a breakdown (1-specificity). The use of this risk scoring system within RBT has the potential to reduce infected cattle movements; however, there are cost implications in ensuring that the information underpinning any system is accurate and up to date. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

2014-05-01

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

Modular and configurable optimal sequence alignment software: Cola.

PubMed

Zamani, Neda; Sundström, Görel; Höppner, Marc P; Grabherr, Manfred G

2014-01-01

The fundamental challenge in optimally aligning homologous sequences is to define a scoring scheme that best reflects the underlying biological processes. Maximising the overall number of matches in the alignment does not always reflect the patterns by which nucleotides mutate. Efficiently implemented algorithms that can be parameterised to accommodate more complex non-linear scoring schemes are thus desirable. We present Cola, alignment software that implements different optimal alignment algorithms, also allowing for scoring contiguous matches of nucleotides in a nonlinear manner. The latter places more emphasis on short, highly conserved motifs, and less on the surrounding nucleotides, which can be more diverged. To illustrate the differences, we report results from aligning 14,100 sequences from 3' untranslated regions of human genes to 25 of their mammalian counterparts, where we found that a nonlinear scoring scheme is more consistent than a linear scheme in detecting short, conserved motifs. Cola is freely available under LPGL from https://github.com/nedaz/cola.

High-throughput purification of recombinant proteins using self-cleaving intein tags.

PubMed

Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

2017-01-01

High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings

NASA Astrophysics Data System (ADS)

Slavakis, Konstantinos; Theodoridis, Sergios

2008-12-01

Very recently, a solution to the kernel-based online classification problem has been given by the adaptive projected subgradient method (APSM). The developed algorithm can be considered as a generalization of a kernel affine projection algorithm (APA) and the kernel normalized least mean squares (NLMS). Furthermore, sparsification of the resulting kernel series expansion was achieved by imposing a closed ball (convex set) constraint on the norm of the classifiers. This paper presents another sparsification method for the APSM approach to the online classification task by generating a sequence of linear subspaces in a reproducing kernel Hilbert space (RKHS). To cope with the inherent memory limitations of online systems and to embed tracking capabilities to the design, an upper bound on the dimension of the linear subspaces is imposed. The underlying principle of the design is the notion of projection mappings. Classification is performed by metric projection mappings, sparsification is achieved by orthogonal projections, while the online system's memory requirements and tracking are attained by oblique projections. The resulting sparsification scheme shows strong similarities with the classical sliding window adaptive schemes. The proposed design is validated by the adaptive equalization problem of a nonlinear communication channel, and is compared with classical and recent stochastic gradient descent techniques, as well as with the APSM's solution where sparsification is performed by a closed ball constraint on the norm of the classifiers.

Assisted Design of Antibody and Protein Therapeutics (ADAPT)

PubMed Central

Vivcharuk, Victor; Baardsnes, Jason; Deprez, Christophe; Sulea, Traian; Jaramillo, Maria; Corbeil, Christopher R.; Mullick, Alaka; Magoon, Joanne; Marcil, Anne; Durocher, Yves; O’Connor-McCourt, Maureen D.

2017-01-01

Effective biologic therapeutics require binding affinities that are fine-tuned to their disease-related molecular target. The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform aids in the selection of mutants that improve/modulate the affinity of antibodies and other biologics. It uses a consensus z-score from three scoring functions and interleaves computational predictions with experimental validation, significantly enhancing the robustness of the design and selection of mutants. The platform was tested on three antibody Fab-antigen systems that spanned a wide range of initial binding affinities: bH1-VEGF-A (44 nM), bH1-HER2 (3.6 nM) and Herceptin-HER2 (0.058 nM). Novel triple mutants were obtained that exhibited 104-, 46- and 32-fold improvements in binding affinity for each system, respectively. Moreover, for all three antibody-antigen systems over 90% of all the intermediate single and double mutants that were designed and tested showed higher affinities than the parent sequence. The contributions of the individual mutants to the change in binding affinity appear to be roughly additive when combined to form double and triple mutants. The new interactions introduced by the affinity-enhancing mutants included long-range electrostatics as well as short-range nonpolar interactions. This diversity in the types of new interactions formed by the mutants was reflected in SPR kinetics that showed that the enhancements in affinities arose from increasing on-rates, decreasing off-rates or a combination of the two effects, depending on the mutation. ADAPT is a very focused search of sequence space and required only 20–30 mutants for each system to be made and tested to achieve the affinity enhancements mentioned above. PMID:28750054

Docking and scoring in virtual screening for drug discovery: methods and applications.

PubMed

Kitchen, Douglas B; Decornez, Hélène; Furr, John R; Bajorath, Jürgen

2004-11-01

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment

NASA Astrophysics Data System (ADS)

Gundreddy, Rohith Reddy; Tan, Maxine; Qui, Yuchen; Zheng, Bin

2015-03-01

The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.

PubMed

Lundegaard, Claus; Lamberth, Kasper; Harndahl, Mikkel; Buus, Søren; Lund, Ole; Nielsen, Morten

2008-07-01

NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8-11 for all 122 alleles. artificial neural network predictions are given as actual IC(50) values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75-80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.

Parallel screening of drug-like natural compounds using Caco-2 cell permeability QSAR model with applicability domain, lipophilic ligand efficiency index and shape property: A case study of HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Patel, Rikin D.; Kumar, Sivakumar Prasanth; Patel, Chirag N.; Shankar, Shetty Shilpa; Pandya, Himanshu A.; Solanki, Hitesh A.

2017-10-01

The traditional drug design strategy centrally focuses on optimizing binding affinity with the receptor target and evaluates pharmacokinetic properties at a later stage which causes high rate of attrition in clinical trials. Alternatively, parallel screening allows evaluation of these properties and affinity simultaneously. In a case study to identify leads from natural compounds with experimental HIV-1 reverse transcriptase (RT) inhibition, we integrated various computational approaches including Caco-2 cell permeability QSAR model with applicability domain (AD) to recognize drug-like natural compounds, molecular docking to study HIV-1 RT interactions and shape similarity analysis with known crystal inhibitors having characteristic butterfly-like model. Further, the lipophilic properties of the compounds refined from the process with best scores were examined using lipophilic ligand efficiency (LLE) index. Seven natural compound hits viz. baicalien, (+)-calanolide A, mniopetal F, fagaronine chloride, 3,5,8-trihydroxy-4-quinolone methyl ether derivative, nitidine chloride and palmatine, were prioritized based on LLE score which demonstrated Caco-2 well absorption labeling, encompassment in AD structural coverage, better receptor affinity, shape adaptation and permissible AlogP value. We showed that this integrative approach is successful in lead exploration of natural compounds targeted against HIV-1 RT enzyme.

[Molecular docking of chlorogenic acid, 3,4-di-O-caffeoylquinic acid and 3,5-di-O-caffeoylquinic acid with human serum albumin].

PubMed

Zhou, Jing; Ma, Hong-yue; Fan, Xin-sheng; Xiao, Wei; Wang, Tuan-jie

2012-10-01

To investigate the mechanism of binding of human serum albumin (HSA) with potential sensitinogen, including chlorogenic acid and two isochlorogenic acids (3,4-di-O-caffeoylquinic acid and 3,5-di-O-caffeoylquinic acid). By using the docking algorithm of computer-aided molecular design and the Molegro Virtual Docker, the crystal structures of HSA with warfarin and diazepam (Protein Data Bank ID: 2BXD and 2BXF) were selected as molecular docking receptors of HSA sites I and II. According to docking scores, key residues and H-bond, the molecular docking mode was selected and confirmed. The molecular docking of chlorogenic acid and two isochlorogenic acids on sites I and II was compared based on the above design. The results from molecular docking indicated that chlorogenic acid, 3,4-di-O-caffeoylquinic acid and 3,5-di-O-caffeoylquinic acid could bind to HSA site I by high affinity scores of -112.3, -155.3 and -153.1, respectively. They could bind to site II on HSA by high affinity scores of -101.7, -138.5 and -133.4, respectively. In site I, two isochlorogenic acids interacted with the key apolar side-chains of Leu238 and Ala291 by higher affinity scores than chlorogenic acid. Furthermore, the H-bonds of isochlorogenic acids with polar residues inside the pocket and at the entrance of the pocket were different from chlorogenic acid. Moreover, the second coffee acyl of isochlorogenic acid occupied the right-hand apolar compartment in the pocket of HSA site I. In site I, the second coffee acyl of isochlorogenic acid formed the H-bonds with polar side-chains, which contributed isochlorogenic acid to binding with site II of HSA. The isochlorogenic acids with two coffee acyls have higher binding abilities with HSA than chlorogenic acid with one coffee acyl, suggesting that isochlorogenic acids binding with HSA may be sensitinogen.

Medical image registration based on normalized multidimensional mutual information

NASA Astrophysics Data System (ADS)

Li, Qi; Ji, Hongbing; Tong, Ming

2009-10-01

Registration of medical images is an essential research topic in medical image processing and applications, and especially a preliminary and key step for multimodality image fusion. This paper offers a solution to medical image registration based on normalized multi-dimensional mutual information. Firstly, affine transformation with translational and rotational parameters is applied to the floating image. Then ordinal features are extracted by ordinal filters with different orientations to represent spatial information in medical images. Integrating ordinal features with pixel intensities, the normalized multi-dimensional mutual information is defined as similarity criterion to register multimodality images. Finally the immune algorithm is used to search registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

A multistage approach to improve performance of computer-aided detection of pulmonary embolisms depicted on CT images: preliminary investigation.

PubMed

Park, Sang Cheol; Chapman, Brian E; Zheng, Bin

2011-06-01

This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.

A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach

NASA Astrophysics Data System (ADS)

Wang, Yu; Guo, Yanzhi; Kuang, Qifan; Pu, Xuemei; Ji, Yue; Zhang, Zhihang; Li, Menglong

2015-04-01

The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast prediction of the binding affinity with promising results, but most of them were developed as all-purpose models despite of the specific functions of different protein families, since proteins from different function families always have different structures and physicochemical features. In this study, we proposed a random forest method to predict the protein-ligand binding affinity based on a comprehensive feature set covering protein sequence, binding pocket, ligand structure and intermolecular interaction. Feature processing and compression was respectively implemented for different protein family datasets, which indicates that different features contribute to different models, so individual representation for each protein family is necessary. Three family-specific models were constructed for three important protein target families of HIV-1 protease, trypsin and carbonic anhydrase respectively. As a comparison, two generic models including diverse protein families were also built. The evaluation results show that models on family-specific datasets have the superior performance to those on the generic datasets and the Pearson and Spearman correlation coefficients ( R p and Rs) on the test sets are 0.740, 0.874, 0.735 and 0.697, 0.853, 0.723 for HIV-1 protease, trypsin and carbonic anhydrase respectively. Comparisons with the other methods further demonstrate that individual representation and model construction for each protein family is a more reasonable way in predicting the affinity of one particular protein family.

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

Anions mediate ligand binding in Adineta vaga glutamate receptor ion channels

PubMed Central

Lomash, Suvendu; Chittori, Sagar; Brown, Patrick; Mayer, Mark L.

2014-01-01

SUMMARY AvGluR1, a glutamate receptor ion channel from the primitive eukaryote Adineta vaga, is activated by alanine, cysteine, methionine and phenylalanine which produce lectin-sensitive desensitizing responses like those to glutamate, aspartate and serine. AvGluR1 LBD crystal structures reveal a novel scheme for binding dissimilar ligands that may be utilized by distantly related odorant/chemosensory receptors. Arginine residues in domain 2 coordinate the γ-carboxyl group of glutamate, while in the alanine, methionine and serine complexes a chloride ion acts as a surrogate ligand, replacing the γ-carboxyl group. Removal of Cl− lowers affinity for these ligands, but not for glutamate, aspartate or for phenylalanine which occludes the anion binding site and binds with low affinity. AvGluR1 LBD crystal structures and sedimentation analysis also provide insights into the evolutionary link between prokaryotic and eukaryotic iGluRs and reveal features unique to both classes, emphasizing the need for additional structure based studies on iGluR-ligand interactions. PMID:23434404

Automated identification of sleep states from EEG signals by means of ensemble empirical mode decomposition and random under sampling boosting.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2017-03-01

Automatic sleep staging is essential for alleviating the burden of the physicians of analyzing a large volume of data by visual inspection. It is also a precondition for making an automated sleep monitoring system feasible. Further, computerized sleep scoring will expedite large-scale data analysis in sleep research. Nevertheless, most of the existing works on sleep staging are either multichannel or multiple physiological signal based which are uncomfortable for the user and hinder the feasibility of an in-home sleep monitoring device. So, a successful and reliable computer-assisted sleep staging scheme is yet to emerge. In this work, we propose a single channel EEG based algorithm for computerized sleep scoring. In the proposed algorithm, we decompose EEG signal segments using Ensemble Empirical Mode Decomposition (EEMD) and extract various statistical moment based features. The effectiveness of EEMD and statistical features are investigated. Statistical analysis is performed for feature selection. A newly proposed classification technique, namely - Random under sampling boosting (RUSBoost) is introduced for sleep stage classification. This is the first implementation of EEMD in conjunction with RUSBoost to the best of the authors' knowledge. The proposed feature extraction scheme's performance is investigated for various choices of classification models. The algorithmic performance of our scheme is evaluated against contemporary works in the literature. The performance of the proposed method is comparable or better than that of the state-of-the-art ones. The proposed algorithm gives 88.07%, 83.49%, 92.66%, 94.23%, and 98.15% for 6-state to 2-state classification of sleep stages on Sleep-EDF database. Our experimental outcomes reveal that RUSBoost outperforms other classification models for the feature extraction framework presented in this work. Besides, the algorithm proposed in this work demonstrates high detection accuracy for the sleep states S1 and REM. Statistical moment based features in the EEMD domain distinguish the sleep states successfully and efficaciously. The automated sleep scoring scheme propounded herein can eradicate the onus of the clinicians, contribute to the device implementation of a sleep monitoring system, and benefit sleep research. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

What Are Error Rates for Classifying Teacher and School Performance Using Value-Added Models?

ERIC Educational Resources Information Center

Schochet, Peter Z.; Chiang, Hanley S.

2013-01-01

This article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using a realistic performance measurement system scheme based on hypothesis testing, the authors develop error rate formulas based on ordinary least squares and…

Implementation and benchmark of a long-range corrected functional in the density functional based tight-binding method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lutsker, V.; Niehaus, T. A., E-mail: thomas.niehaus@physik.uni-regensburg.de; Aradi, B.

2015-11-14

Bridging the gap between first principles methods and empirical schemes, the density functional based tight-binding method (DFTB) has become a versatile tool in predictive atomistic simulations over the past years. One of the major restrictions of this method is the limitation to local or gradient corrected exchange-correlation functionals. This excludes the important class of hybrid or long-range corrected functionals, which are advantageous in thermochemistry, as well as in the computation of vibrational, photoelectron, and optical spectra. The present work provides a detailed account of the implementation of DFTB for a long-range corrected functional in generalized Kohn-Sham theory. We apply themore » method to a set of organic molecules and compare ionization potentials and electron affinities with the original DFTB method and higher level theory. The new scheme cures the significant overpolarization in electric fields found for local DFTB, which parallels the functional dependence in first principles density functional theory (DFT). At the same time, the computational savings with respect to full DFT calculations are not compromised as evidenced by numerical benchmark data.« less

Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays.

PubMed

Wang, Min; Ge, Shuzhi Sam; Hong, Keum-Shik

2010-11-01

This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. To overcome the design difficulty from non-affine structure of pure-feedback system, mean value theorem is exploited to deduce affine appearance of state variables x(i) as virtual controls α(i), and of the actual control u. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. The novel Lyapunov-Krasovskii functionals are employed to compensate for the unknown functions of current delayed state, which is effectively free from any restriction on unknown time-delay functions and overcomes the circular construction of controller caused by the neural approximation of a function of u and [Formula: see text] . Novel continuous functions are introduced to overcome the design difficulty deduced from the use of one adaptive parameter. To achieve uniformly ultimate boundedness of all the signals in the closed-loop system and tracking performance, control gains are effectively modified as a dynamic form with a class of even function, which makes stability analysis be carried out at the present of multiple time-varying delays. Simulation studies are provided to demonstrate the effectiveness of the proposed scheme.

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

PubMed

Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

PubMed

Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for future ligand design in lead optimization procedures. The approach can readily be extended to evaluate the binding affinities of a series of protein-protein complexes. (c) 2007 Wiley-Liss, Inc.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Deng, Nanjie; Flynn, William F.; Xia, Junchao; Vijayan, R. S. K.; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M.

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

PubMed

Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

2016-05-01

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

Data Independent Acquisition analysis in ProHits 4.0.

PubMed

Liu, Guomin; Knight, James D R; Zhang, Jian Ping; Tsou, Chih-Chiang; Wang, Jian; Lambert, Jean-Philippe; Larsen, Brett; Tyers, Mike; Raught, Brian; Bandeira, Nuno; Nesvizhskii, Alexey I; Choi, Hyungwon; Gingras, Anne-Claude

2016-10-21

Affinity purification coupled with mass spectrometry (AP-MS) is a powerful technique for the identification and quantification of physical interactions. AP-MS requires careful experimental design, appropriate control selection and quantitative workflows to successfully identify bona fide interactors amongst a large background of contaminants. We previously introduced ProHits, a Laboratory Information Management System for interaction proteomics, which tracks all samples in a mass spectrometry facility, initiates database searches and provides visualization tools for spectral counting-based AP-MS approaches. More recently, we implemented Significance Analysis of INTeractome (SAINT) within ProHits to provide scoring of interactions based on spectral counts. Here, we provide an update to ProHits to support Data Independent Acquisition (DIA) with identification software (DIA-Umpire and MSPLIT-DIA), quantification tools (through DIA-Umpire, or externally via targeted extraction), and assessment of quantitative enrichment (through mapDIA) and scoring of interactions (through SAINT-intensity). With additional improvements, notably support of the iProphet pipeline, facilitated deposition into ProteomeXchange repositories and enhanced export and viewing functions, ProHits 4.0 offers a comprehensive suite of tools to facilitate affinity proteomics studies. It remains challenging to score, annotate and analyze proteomics data in a transparent manner. ProHits was previously introduced as a LIMS to enable storing, tracking and analysis of standard AP-MS data. In this revised version, we expand ProHits to include integration with a number of identification and quantification tools based on Data-Independent Acquisition (DIA). ProHits 4.0 also facilitates data deposition into public repositories, and the transfer of data to new visualization tools. Copyright © 2016 Elsevier B.V. All rights reserved.

Stepwise identification of HLA-A*0201-restricted CD8+ T-cell epitope peptides from herpes simplex virus type 1 genome boosted by a StepRank scheme.

PubMed

Bi, Jianjun; Song, Rengang; Yang, Huilan; Li, Bingling; Fan, Jianyong; Liu, Zhongrong; Long, Chaoqin

2011-01-01

Identification of immunodominant epitopes is the first step in the rational design of peptide vaccines aimed at T-cell immunity. To date, however, it is yet a great challenge for accurately predicting the potent epitope peptides from a pool of large-scale candidates with an efficient manner. In this study, a method that we named StepRank has been developed for the reliable and rapid prediction of binding capabilities/affinities between proteins and genome-wide peptides. In this procedure, instead of single strategy used in most traditional epitope identification algorithms, four steps with different purposes and thus different computational demands are employed in turn to screen the large-scale peptide candidates that are normally generated from, for example, pathogenic genome. The steps 1 and 2 aim at qualitative exclusion of typical nonbinders by using empirical rule and linear statistical approach, while the steps 3 and 4 focus on quantitative examination and prediction of the interaction energy profile and binding affinity of peptide to target protein via quantitative structure-activity relationship (QSAR) and structure-based free energy analysis. We exemplify this method through its application to binding predictions of the peptide segments derived from the 76 known open-reading frames (ORFs) of herpes simplex virus type 1 (HSV-1) genome with or without affinity to human major histocompatibility complex class I (MHC I) molecule HLA-A*0201, and find that the predictive results are well compatible with the classical anchor residue theory and perfectly match for the extended motif pattern of MHC I-binding peptides. The putative epitopes are further confirmed by comparisons with 11 experimentally measured HLA-A*0201-restrcited peptides from the HSV-1 glycoproteins D and K. We expect that this well-designed scheme can be applied in the computational screening of other viral genomes as well.

Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study

PubMed Central

Lip, Gregory Y H; Hansen, Morten Lock; Hansen, Peter Riis; Tolstrup, Janne Schurmann; Lindhardsen, Jesper; Selmer, Christian; Ahlehoff, Ole; Olsen, Anne-Marie Schjerning; Gislason, Gunnar Hilmar; Torp-Pedersen, Christian

2011-01-01

Objectives To evaluate the individual risk factors composing the CHADS2 (Congestive heart failure, Hypertension, Age≥75 years, Diabetes, previous Stroke) score and the CHA2DS2-VASc (CHA2DS2-Vascular disease, Age 65-74 years, Sex category) score and to calculate the capability of the schemes to predict thromboembolism. Design Registry based cohort study. Setting Nationwide data on patients admitted to hospital with atrial fibrillation. Population All patients with atrial fibrillation not treated with vitamin K antagonists in Denmark in the period 1997-2006. Main outcome measures Stroke and thromboembolism. Results Of 121 280 patients with non-valvular atrial fibrillation, 73 538 (60.6%) fulfilled the study inclusion criteria. In patients at “low risk” (score=0), the rate of thromboembolism per 100 person years was 1.67 (95% confidence interval 1.47 to 1.89) with CHADS2 and 0.78 (0.58 to 1.04) with CHA2DS2-VASc at one year’s follow-up. In patients at “intermediate risk” (score=1), this rate was 4.75 (4.45 to 5.07) with CHADS2 and 2.01 (1.70 to 2.36) with CHA2DS2-VASc. The rate of thromboembolism depended on the individual risk factors composing the scores, and both schemes underestimated the risk associated with previous thromboembolic events. When patients were categorised into low, intermediate, and high risk groups, C statistics at 10 years’ follow-up were 0.812 (0.796 to 0.827) with CHADS2 and 0.888 (0.875 to 0.900) with CHA2DS2-VASc. Conclusions The risk associated with a specific risk stratification score depended on the risk factors composing the score. CHA2DS2-VASc performed better than CHADS2 in predicting patients at high risk, and those categorised as low risk by CHA2DS2-VASc were truly at low risk for thromboembolism. PMID:21282258

Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study.

PubMed

Olesen, Jonas Bjerring; Lip, Gregory Y H; Hansen, Morten Lock; Hansen, Peter Riis; Tolstrup, Janne Schurmann; Lindhardsen, Jesper; Selmer, Christian; Ahlehoff, Ole; Olsen, Anne-Marie Schjerning; Gislason, Gunnar Hilmar; Torp-Pedersen, Christian

2011-01-31

To evaluate the individual risk factors composing the CHADS(2) (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, previous Stroke) score and the CHA(2)DS(2)-VASc (CHA(2)DS(2)-Vascular disease, Age 65-74 years, Sex category) score and to calculate the capability of the schemes to predict thromboembolism. Registry based cohort study. Nationwide data on patients admitted to hospital with atrial fibrillation. Population All patients with atrial fibrillation not treated with vitamin K antagonists in Denmark in the period 1997-2006. Stroke and thromboembolism. Of 121,280 patients with non-valvular atrial fibrillation, 73,538 (60.6%) fulfilled the study inclusion criteria. In patients at "low risk" (score = 0), the rate of thromboembolism per 100 person years was 1.67 (95% confidence interval 1.47 to 1.89) with CHADS(2) and 0.78 (0.58 to 1.04) with CHA(2)DS(2)-VASc at one year's follow-up. In patients at "intermediate risk" (score = 1), this rate was 4.75 (4.45 to 5.07) with CHADS(2) and 2.01 (1.70 to 2.36) with CHA(2)DS(2)-VASc. The rate of thromboembolism depended on the individual risk factors composing the scores, and both schemes underestimated the risk associated with previous thromboembolic events. When patients were categorised into low, intermediate, and high risk groups, C statistics at 10 years' follow-up were 0.812 (0.796 to 0.827) with CHADS(2) and 0.888 (0.875 to 0.900) with CHA(2)DS(2)-VASc. The risk associated with a specific risk stratification score depended on the risk factors composing the score. CHA(2)DS(2)-VASc performed better than CHADS(2) in predicting patients at high risk, and those categorised as low risk by CHA(2)DS(2)-VASc were truly at low risk for thromboembolism.

Affinity monolith chromatography: A review of general principles and applications.

PubMed

Li, Zhao; Rodriguez, Elliott; Azaria, Shiden; Pekarek, Allegra; Hage, David S

2017-11-01

Affinity monolith chromatography, or AMC, is a liquid chromatographic method in which the support is a monolith and the stationary phase is a biological-binding agent or related mimic. AMC has become popular for the isolation of biochemicals, for the measurement of various analytes, and for studying biological interactions. This review will examine the principles and applications of AMC. The materials that have been used to prepare AMC columns will be discussed, which have included various organic polymers, silica, agarose, and cryogels. Immobilization schemes that have been used in AMC will also be considered. Various binding agents and applications that have been reported for AMC will then be described. These applications will include the use of AMC for bioaffinity chromatography, immunoaffinity chromatography, dye-ligand affinity chromatography, and immobilized metal-ion affinity chromatography. The use of AMC with chiral stationary phases and as a tool to characterize biological interactions will also be examined. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Randomized Controlled Study on Safety and Feasibility of Transfusion Trigger Score of Emergency Operations.

PubMed

Liu, De-Xing; Liu, Jin; Zhang, Fan; Zhang, Qiu-Ying; Xie, Mian; Zhu, Zhao-Qiong

2015-07-05

Due to the floating of the guideline, there is no evidence-based evaluation index on when to start the blood transfusion for patients with hemoglobin (Hb) level between 7 and 10 g/dl. As a result, the trigger point of blood transfusion may be different in the emergency use of the existing transfusion guidelines. The present study was designed to evaluate whether the scheme can be safely and effectively used for emergency patients, so as to be supported by multicenter and large sample data in the future. From June 2013 to June 2014, patients were randomly divided into the experimental group (Peri-operative Transfusion Trigger Score of Emergency [POTTS-E] group) and the control group (control group). The between-group differences in the patients' demography and baseline information, mortality and blood transfusion-related complications, heart rate, resting arterial pressure, body temperature, and Hb values were compared. The consistency of red blood cell (RBC) transfusion standards of the two groups of patients with the current blood transfusion guideline, namely the compliance of the guidelines, utilization rate, and per-capita consumption of autologous RBC were analyzed. During the study period, a total of 72 patients were recorded, and 65 of them met the inclusion criteria, which included 33 males and 32 females with a mean age of (34.8 ± 14.6) years. 50 underwent abdomen surgery, 4 underwent chest surgery, 11 underwent arms and legs surgery. There was no statistical difference between the two groups for demography and baseline information. There was also no statistical differences between the two groups in anesthesia time, intraoperative rehydration, staying time in postanesthetic care unit, emergency hospitalization, postoperative 72 h Acute Physiologic Assessment and Chronic Health Evaluation II scores, blood transfusion-related complications and mortality. Only the POTTS-E group on the 1 st postoperative day Hb was lower than group control, P < 0.05. POTTS-E group was totally (100%) conformed to the requirements of the transfusion guideline to RBC infusion, which was higher than that of the control group (81.25%), P < 0.01.There were no statistical differences in utilization rates of autologous blood of the two groups; the utilization rates of allogeneic RBC, total allogeneic RBC and total RBC were 48.48%, 51.5%, and 75.7% in POTTS-E group, which were lower than those of the control group (84.3%, 84.3%, and 96.8%) P < 0.05 or P < 0.01. Per capita consumption of intraoperative allogeneic RBC, total allogeneic RBC and total RBC were 0 (0, 3.0), 2.0 (0, 4.0), and 3.1 (0.81, 6.0) in POTTS-E groups were all lower than those of control group (4.0 [2.0, 4.0], 4.0 [2.0, 6.0] and 5.8 [2.7, 8.2]), P < 0.05 or P < 0.001. Peri-operative Transfusion Trigger Score-E evaluation scheme is used to guide the application of RBC. There are no differences in the recent prognosis of patients with the traditional transfusion guidelines. This scheme is safe; Compared with doctor experience-based subjective assessment, the scoring scheme was closer to patient physiological needs for transfusion and more reasonable; Utilization rate and the per capita consumption of RBC are obviously declined, which has clinical significance and is feasible. Based on the abovementioned three points, POTTS-E scores scheme is safe, reasonable, and practicable and has the value for carrying out multicenter and large sample clinical researches.

A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Riette, Sébastien; Lac, Christine

2016-08-01

In the Application of Research to Operations at Mesoscale (AROME) numerical weather forecast model used in operations at Météo-France, five mass-flux schemes are available to parametrize shallow convection at kilometre resolution. All but one are based on the eddy-diffusivity-mass-flux approach, and differ in entrainment/detrainment, the updraft vertical velocity equation and the closure assumption. The fifth is based on a more classical mass-flux approach. Screen-level scores obtained with these schemes show few discrepancies and are not sufficient to highlight behaviour differences. Here, we describe and use a new experimental framework, able to compare and discriminate among different schemes. For a year, daily forecast experiments were conducted over small domains centred on the five French metropolitan radio-sounding locations. Cloud base, planetary boundary-layer height and normalized vertical profiles of specific humidity, potential temperature, wind speed and cloud condensate were compared with observations, and with each other. The framework allowed the behaviour of the different schemes in and above the boundary layer to be characterized. In particular, the impact of the entrainment/detrainment formulation, closure assumption and cloud scheme were clearly visible. Differences mainly concerned the transport intensity thus allowing schemes to be separated into two groups, with stronger or weaker updrafts. In the AROME model (with all interactions and the possible existence of compensating errors), evaluation diagnostics gave the advantage to the first group.

Knowledge-based grouping of modeled HLA peptide complexes.

PubMed

Kangueane, P; Sakharkar, M K; Lim, K S; Hao, H; Lin, K; Chee, R E; Kolatkar, P R

2000-05-01

Human leukocyte antigens are the most polymorphic of human genes and multiple sequence alignment shows that such polymorphisms are clustered in the functional peptide binding domains. Because of such polymorphism among the peptide binding residues, the prediction of peptides that bind to specific HLA molecules is very difficult. In recent years two different types of computer based prediction methods have been developed and both the methods have their own advantages and disadvantages. The nonavailability of allele specific binding data restricts the use of knowledge-based prediction methods for a wide range of HLA alleles. Alternatively, the modeling scheme appears to be a promising predictive tool for the selection of peptides that bind to specific HLA molecules. The scoring of the modeled HLA-peptide complexes is a major concern. The use of knowledge based rules (van der Waals clashes and solvent exposed hydrophobic residues) to distinguish binders from nonbinders is applied in the present study. The rules based on (1) number of observed atomic clashes between the modeled peptide and the HLA structure, and (2) number of solvent exposed hydrophobic residues on the modeled peptide effectively discriminate experimentally known binders from poor/nonbinders. Solved crystal complexes show no vdW Clash (vdWC) in 95% cases and no solvent exposed hydrophobic peptide residues (SEHPR) were seen in 86% cases. In our attempt to compare experimental binding data with the predicted scores by this scoring scheme, 77% of the peptides are correctly grouped as good binders with a sensitivity of 71%.

The assessment of post-vasectomy pain in mice using behaviour and the Mouse Grimace Scale.

PubMed

Leach, Matthew C; Klaus, Kristel; Miller, Amy L; Scotto di Perrotolo, Maud; Sotocinal, Susana G; Flecknell, Paul A

2012-01-01

Current behaviour-based pain assessments for laboratory rodents have significant limitations. Assessment of facial expression changes, as a novel means of pain scoring, may overcome some of these limitations. The Mouse Grimace Scale appears to offer a means of assessing post-operative pain in mice that is as effective as manual behavioural-based scoring, without the limitations of such schemes. Effective assessment of post-operative pain is not only critical for animal welfare, but also the validity of science using animal models. This study compared changes in behaviour assessed using both an automated system ("HomeCageScan") and using manual analysis with changes in facial expressions assessed using the Mouse Grimace Scale (MGS). Mice (n = 6/group) were assessed before and after surgery (scrotal approach vasectomy) and either received saline, meloxicam or bupivacaine. Both the MGS and manual scoring of pain behaviours identified clear differences between the pre and post surgery periods and between those animals receiving analgesia (20 mg/kg meloxicam or 5 mg/kg bupivacaine) or saline post-operatively. Both of these assessments were highly correlated with those showing high MGS scores also exhibiting high frequencies of pain behaviours. Automated behavioural analysis in contrast was only able to detect differences between the pre and post surgery periods. In conclusion, both the Mouse Grimace Scale and manual scoring of pain behaviours are assessing the presence of post-surgical pain, whereas automated behavioural analysis could be detecting surgical stress and/or post-surgical pain. This study suggests that the Mouse Grimace Scale could prove to be a quick and easy means of assessing post-surgical pain, and the efficacy of analgesic treatment in mice that overcomes some of the limitations of behaviour-based assessment schemes.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

Role of binding entropy in the refinement of protein-ligand docking predictions: analysis based on the use of 11 scoring functions.

PubMed

Ruvinsky, Anatoly M

2007-06-01

We present results of testing the ability of eleven popular scoring functions to predict native docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput Chem 2005, 26, 1089) for estimation the entropy contributions of relative motions to protein-ligand binding affinity. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We use a test set of 100 PDB protein-ligand complexes and ensembles of 101 docked positions generated by (Wang et al. J Med Chem 2003, 46, 2287) for each ligand in the test set. To test the suggested method we compared the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock scoring function, by 2-25% with G-Score, by 7-41% with D-Score, by 0-8% with LigScore, by 1-6% with PLP, by 0-12% with LUDI, by 2-8% with F-Score, by 7-29% with ChemScore, by 0-9% with X-Score, by 2-19% with PMF, and by 1-7% with DrugScore. We also compared the performance of the suggested method with the method based on ranking by cluster occupancy only. We analyze how the choice of a clustering-RMSD and a low bound of dense clusters impacts on docking accuracy of the scoring methods. We derive optimal intervals of the clustering-RMSD for 11 scoring functions.

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets.

PubMed

Xu, Weijun; Lucke, Andrew J; Fairlie, David P

2015-04-01

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

The Tautomeric Equilibria of Thio-Analogues of Nucleic Acid Bases. Part 1. 2-Thiouracil: Background, Preparation of Model Compounds, and Gas Phase Proton Affinities

DTIC Science & Technology

1989-05-11

complilmentary publication for the present paper has studied the tautomeric equilibria by infrared spectroscopy . (Scheme 2 ) 5 Preparation of Compounds...4 6 292-2940C). 14 2 -Methylthio-4- pyrimidone (6).- To 2 -thiouracil (4) (12.8 g, 0.1 mol) and NaOH (7.6 g, 0.19 mol) in 200 ml of H20-EtOH (I : 1... pyrimidone (1i).- To a solution of 5N NaOH (44 ml, 220 mmol) containing 2 -thiouracil (4) (10.0 g, 78.0 mmol) at 0 CC was added dropwise dimethyl

Effect of modified atmosphere packaging on Quality Index Method (QIM) scores of farmed gilthead seabream (Sparus aurata L.) at low and abused temperatures.

PubMed

Campus, Marco; Bonaglini, Elia; Cappuccinelli, Roberto; Porcu, Maria Cristina; Tonelli, Roberto; Roggio, Tonina

2011-04-01

A Quality Index Method (QIM) scheme was developed for modified atmosphere packaging (MAP) packed gilthead seabream, and the effect of MAP gas mixtures (60% CO2 and 40% N2; 60% CO2, 30% O2, and 10% N2), temperature (2, 4, and 8 °C), and time of storage on QI scores was assessed. QI scores were crossed with sensory evaluation of cooked fish according to a modified Torry scheme to establish the rejection point. In order to reduce redundant parameters, a principal component analysis was applied on preliminary QIM parameters scores coming from the best performing MAP among those tested. The final QIM scheme consists of 13 parameters and a maximum demerit score of 25. The maximum storage time was found to be 13 d at 4 °C for MAP 60% CO2 and 40% N2. Storage at 2 °C do not substantially improved sensory parameters scores, while storage under temperature abuse (8 °C) accelerated drastically the rate of increase of QI scores and reduced the maximum storage time to 6 d.

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

Test Information Targeting Strategies for Adaptive Multistage Testing Designs.

ERIC Educational Resources Information Center

Luecht, Richard M.; Burgin, William

Adaptive multistage testlet (MST) designs appear to be gaining popularity for many large-scale computer-based testing programs. These adaptive MST designs use a modularized configuration of preconstructed testlets and embedded score-routing schemes to prepackage different forms of an adaptive test. The conditional information targeting (CIT)…

River Pollution: Part II. Biological Methods for Assessing Water Quality.

ERIC Educational Resources Information Center

Openshaw, Peter

1984-01-01

Discusses methods used in the biological assessment of river quality and such indicators of clean and polluted waters as the Trent Biotic Index, Chandler Score System, and species diversity indexes. Includes a summary of a river classification scheme based on quality criteria related to water use. (JN)

Metal-Chelate Affinity Precipitation with Thermo-Responsive Polymer for Purification of ε-Poly-L-Lysine.

PubMed

Li, Sipeng; Ding, Zhaoyang; Liu, Jifu; Cao, Xuejun

2017-12-01

ε-Poly-L-lysine (ε-PL) is a natural preservative for food processing industry. A thermo-responsive polymer, attached with Cu 2+ or Ni 2+ , was prepared for metal-chelate affinity precipitation for purification of ε-PL. The low critical solution temperatures (LCSTs) of these polymers were close to the room temperature (31.0-35.0 °C). The optimal adsorption conditions were as follows: pH 4.0, 0 mol/L NaCl, ligand density 75.00 μmol/g, and 120 min. The ligand Cu 2+ showed a stronger affinity interaction with ε-PL and the highest adsorption amount reached 251.93 mg/g polymer. The elution recovery of ε-PL could be 98.42% with 0.50 mol/L imidazole (pH = 8.0) as the eluent. The method could purify ε-PL from fermentation broth and the final product was proved as electrophoretic pure by SDS-PAGE. Moreover, these affinity polymers could be recycled after the purification of ε-PL and the recoveries were above 95.00%. Graphical Abstract Scheme for affinity precipitation of ε-PL.

Properties of the Narrative Scoring Scheme Using Narrative Retells in Young School-Age Children

ERIC Educational Resources Information Center

Heilmann, John; Miller, Jon F.; Nockerts, Ann; Dunaway, Claudia

2010-01-01

Purpose: To evaluate the clinical utility of the narrative scoring scheme (NSS) as an index of narrative macrostructure for young school-age children. Method: Oral retells of a wordless picture book were elicited from 129 typically developing children, ages 5-7. A series of correlations and hierarchical regression equations were completed using…

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction

PubMed Central

Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J.

2018-01-01

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future. PMID:29538331

The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.

PubMed

Li, Hongjian; Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J

2018-03-14

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future.

A neural network model for credit risk evaluation.

PubMed

Khashman, Adnan

2009-08-01

Credit scoring is one of the key analytical techniques in credit risk evaluation which has been an active research area in financial risk management. This paper presents a credit risk evaluation system that uses a neural network model based on the back propagation learning algorithm. We train and implement the neural network to decide whether to approve or reject a credit application, using seven learning schemes and real world credit applications from the Australian credit approval datasets. A comparison of the system performance under the different learning schemes is provided, furthermore, we compare the performance of two neural networks; with one and two hidden layers following the ideal learning scheme. Experimental results suggest that neural networks can be effectively used in automatic processing of credit applications.

Gonioscopy in the dog: inter-examiner variability and the search for a grading scheme.

PubMed

Oliver, J A C; Cottrell, B C; Newton, J R; Mellersh, C S

2017-11-01

To investigate inter-examiner variability in gonioscopic evaluation of pectinate ligament abnormality in dogs and to assess level of inter-examiner agreement for four different gonioscopy grading schemes. Two examiners performed gonioscopy in 98 eyes of 49 Welsh springer spaniel dogs and estimated the percentage circumference of iridocorneal angle affected by pectinate ligament abnormality to the nearest 5%. Percentage scores assigned to each eye by the two examiners were compared. Inter-examiner agreement was assessed following assignment of the percentage scores to each of four grading schemes by Cohen's kappa statistic. There was a strong positive correlation between the results of the two examiners (R=0·91). In general, Examiner 1 scored individual eyes higher than Examiner 2, especially for eyes in which both examiners diagnosed pectinate ligament abnormality. A "good" level of agreement could only be achieved with a gonioscopy grading scheme of no more than three categories and with a relatively large intermediate bandwidth (κ=0·68). A three-tiered grading scheme might represent an improvement on hereditary eye disease schemes which simply classify dogs to be either "affected" or "unaffected" for pectinate ligament abnormality. However, the large intermediate bandwidth of this scheme would only allow for the additional detection of those dogs with marked progression of pectinate ligament abnormality which would be considered most at risk of primary closed-angle glaucoma. © 2017 British Small Animal Veterinary Association.

A combination of spin diffusion methods for the determination of protein-ligand complex structural ensembles.

PubMed

Pilger, Jens; Mazur, Adam; Monecke, Peter; Schreuder, Herman; Elshorst, Bettina; Bartoschek, Stefan; Langer, Thomas; Schiffer, Alexander; Krimm, Isabelle; Wegstroth, Melanie; Lee, Donghan; Hessler, Gerhard; Wendt, K-Ulrich; Becker, Stefan; Griesinger, Christian

2015-05-26

Structure-based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin-diffusion-based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein-ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X-ray analysis. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

NASA Technical Reports Server (NTRS)

Rajendran, K.; Krishnamurti, T. N.; Misra, V.; Tao, W.-K.

2004-01-01

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity

PubMed Central

Hayik, Seth A.; Dunbrack, Roland; Merz, Kenneth M.

2010-01-01

Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaining atoms as a fixed charge background for the active site. Such a semi-empirical QM/MM scoring function has been implemented in AMBER using DivCon and tested on a set of 23 metalloprotein-ligand complexes, where QM/MM methods provide a particular advantage in the modeling of the metal ion. The binding affinity of this set of proteins can be calculated with an R2 of 0.64 and a standard deviation of 1.88 kcal/mol without fitting and 0.71 and a standard deviation of 1.69 kcal/mol with fitted weighting of the individual scoring terms. In this study we explore using various methods to calculate terms in the binding free energy equation, including entropy estimates and minimization standards. From these studies we found that using the rotational bond estimate to ligand entropy results in a reasonable R2 of 0.63 without fitting. We also found that using the ESCF energy of the proteins without minimization resulted in an R2 of 0.57, when using the rotatable bond entropy estimate. PMID:21221417

Blinded Prospective Evaluation of Computer-Based Mechanistic Schizophrenia Disease Model for Predicting Drug Response

PubMed Central

Geerts, Hugo; Spiros, Athan; Roberts, Patrick; Twyman, Roy; Alphs, Larry; Grace, Anthony A.

2012-01-01

The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published ‘Quantitative Systems Pharmacology’ computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D2 antagonist and ocaperidone, a very high affinity dopamine D2 antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development. PMID:23251349

Impact of antipsychotic medication on transcranial direct current stimulation (tDCS) effects in schizophrenia patients.

PubMed

Agarwal, Sri Mahavir; Bose, Anushree; Shivakumar, Venkataram; Narayanaswamy, Janardhanan C; Chhabra, Harleen; Kalmady, Sunil V; Varambally, Shivarama; Nitsche, Michael A; Venkatasubramanian, Ganesan; Gangadhar, Bangalore N

2016-01-30

Transcranial direct current stimulation (tDCS) has generated interest as a treatment modality for schizophrenia. Dopamine, a critical pathogenetic link in schizophrenia, is also known to influence tDCS effects. We evaluated the influence of antipsychotic drug type (as defined by dopamine D2 receptor affinity) on the impact of tDCS in schizophrenia. DSM-IV-TR-diagnosed schizophrenia patients [N=36] with persistent auditory hallucinations despite adequate antipsychotic treatment were administered add-on tDCS. Patients were divided into three groups based on the antipsychotic's affinity to D2 receptors. An auditory hallucinations score (AHS) was measured using the auditory hallucinations subscale of the Psychotic Symptom Rating Scales (PSYRATS). Add-on tDCS resulted in a significant reduction inAHS. Antipsychotic drug type had a significant effect on AHS reduction. Patients treated with high affinity antipsychotics showed significantly lesser improvement compared to patients on low affinity antipsychotics or a mixture of the two. Furthermore, a significant sex-by-group interaction occurred; type of medication had an impact on tDCS effects only in women. Improvement differences could be due to the larger availability of the dopamine receptor system in patients taking antipsychotics with low D2 affinity. Sex-specific differences suggest potential estrogen-mediated effects. This study reports a first-time observation on the clinical utility of antipsychotic drug type in predicting tDCS effects in schizophrenia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Versatile and declarative dynamic programming using pair algebras.

PubMed

Steffen, Peter; Giegerich, Robert

2005-09-12

Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes. Based on this programming style, we introduce a generic product operation of scoring schemes. This leads to a remarkable variety of applications, allowing us to achieve optimizations under multiple objective functions, alternative solutions and backtracing, holistic search space analysis, ambiguity checking, and more, without additional programming effort. We demonstrate the method on several applications for RNA secondary structure prediction. The product operation as introduced here adds a significant amount of flexibility to dynamic programming. It provides a versatile testbed for the development of new algorithmic ideas, which can immediately be put to practice.

Evaluation of radiographic interpretation competence of veterinary students in Finland.

PubMed

Koskinen, Heli I; Snellman, Marjatta

2009-01-01

In the evaluation of the clinical competence of veterinary students, many different definitions and methods are approved. Due to the increasing discussion of the quality of outcomes produced by newly graduated veterinarians, methods for the evaluation of clinical competencies should also be evaluated. In this study, this was done by comparing two qualitative evaluation schemes: the well-known structure of observed learning outcome (SOLO) taxonomy and a modification of this taxonomy. A case-based final radiologic examination was selected and the investigation was performed by classifying students' outcomes. These classes were finally put next to original (quantitative) scores and the statistical calculations were initiated. Significant correlations between taxonomies (0.53) and the modified taxonomy and original scores (0.66) were found and some qualitative similarities between evaluation methods were observed. In addition, some supplements were recommended for the structure of evaluation schemes, especially for the structure of the modified SOLO taxonomy.

Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database.

PubMed

Doytchinova, Irini; Atanasova, Mariyana; Valkova, Iva; Stavrakov, Georgi; Philipova, Irena; Zhivkova, Zvetanka; Zheleva-Dimitrova, Dimitrina; Konstantinov, Spiro; Dimitrov, Ivan

2018-12-01

The inhibition of the enzyme acetylcholinesterase (AChE) increases the levels of the neurotransmitter acetylcholine and symptomatically improves the affected cognitive function. In the present study, we searched for novel AChE inhibitors by docking-based virtual screening of the standard lead-like set of ZINC database containing more than 6 million small molecules using GOLD software. The top 10 best-scored hits were tested in vitro for AChE affinity, neurotoxicity, GIT and BBB permeability. The main pharmacokinetic parameters like volume of distribution, free fraction in plasma, total clearance, and half-life were predicted by previously derived models. Nine of the compounds bind to the enzyme with affinities from 0.517 to 0.735 µM, eight of them are non-toxic. All hits permeate GIT and BBB and bind extensively to plasma proteins. Most of them are low-clearance compounds. In total, seven of the 10 hits are promising for further lead optimisation. These are structures with ZINC IDs: 00220177, 44455618, 66142300, 71804814, 72065926, 96007907, and 97159977.

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

NASA Astrophysics Data System (ADS)

Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

2008-09-01

The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.

Towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2013-03-01

Automatic co-alignment of optical and virtual colonoscopy images can supplement traditional endoscopic procedures, by providing more complete information of clinical value to the gastroenterologist. In this work, we present a comparative analysis of our optical flow based technique for colonoscopy tracking, in relation to current state of the art methods, in terms of tracking accuracy, system stability, and computational efficiency. Our optical-flow based colonoscopy tracking algorithm starts with computing multi-scale dense and sparse optical flow fields to measure image displacements. Camera motion parameters are then determined from optical flow fields by employing a Focus of Expansion (FOE) constrained egomotion estimation scheme. We analyze the design choices involved in the three major components of our algorithm: dense optical flow, sparse optical flow, and egomotion estimation. Brox's optical flow method,1 due to its high accuracy, was used to compare and evaluate our multi-scale dense optical flow scheme. SIFT6 and Harris-affine features7 were used to assess the accuracy of the multi-scale sparse optical flow, because of their wide use in tracking applications; the FOE-constrained egomotion estimation was compared with collinear,2 image deformation10 and image derivative4 based egomotion estimation methods, to understand the stability of our tracking system. Two virtual colonoscopy (VC) image sequences were used in the study, since the exact camera parameters(for each frame) were known; dense optical flow results indicated that Brox's method was superior to multi-scale dense optical flow in estimating camera rotational velocities, but the final tracking errors were comparable, viz., 6mm vs. 8mm after the VC camera traveled 110mm. Our approach was computationally more efficient, averaging 7.2 sec. vs. 38 sec. per frame. SIFT and Harris affine features resulted in tracking errors of up to 70mm, while our sparse optical flow error was 6mm. The comparison among egomotion estimation algorithms showed that our FOE-constrained egomotion estimation method achieved the optimal balance between tracking accuracy and robustness. The comparative study demonstrated that our optical-flow based colonoscopy tracking algorithm maintains good accuracy and stability for routine use in clinical practice.

A proposal of linear assessment scheme for the udder of dairy camels (Camelus dromedarius L.).

PubMed

Ayadi, Moez; Aljumaah, Riyadh Saleh; Samara, Emad Mohammed; Faye, Bernard; Caja, Gerardo

2016-06-01

Digital images from the left side of the mammary gland of 146 multiparous lactating dromedary camels in mid lactation and managed under intensive conditions were obtained immediately before milking and used to build up a reference scheme for the morphological evaluation of camel mammary glands. A 5-point linear scoring scheme (with 0.5-point accuracy) was subsequently generated based on five mammary traits (udder, depth and floor inclination, teats, shape, length, and width). Results showed that Arabian dairy camels had voluminous udders with large-sized teats. Most common udder shape was globular (47.3 %), followed by the pear (34.3 %) and pendulous (18.4 %) shapes. Conical- or funnel-shaped teats (60.9 %) were the most frequent, followed by cylindrical- (29.5 %) and blew-up (9.6 %)-shaped teats. The observed variation in the udder and teat measurements, as well as in typology, attested that dromedary camels need especially large milking clusters to improve their machine milkability. Assessment of the previously indicated digital images according to the proposed linear scoring scheme, performed by 3 independent operators showed that the overall means were close to 3.00 points (values between 2.45 and 3.62), and the standard deviations were close to 0.76 points (values between 0.58 and 0.94). Moderate repeatability between operators (r > 0.69) was obtained for udder depth and floor inclination, indicating that training of operators, as well as improvements in the definition of traits should be considered in future studies. Further research is needed to validate the proposed linear scoring system in different stages of lactation and parities using a large number of camels.

Elastic models: a comparative study applied to retinal images.

PubMed

Karali, E; Lambropoulou, S; Koutsouris, D

2011-01-01

In this work various methods of parametric elastic models are compared, namely the classical snake, the gradient vector field snake (GVF snake) and the topology-adaptive snake (t-snake), as well as the method of self-affine mapping system as an alternative to elastic models. We also give a brief overview of the methods used. The self-affine mapping system is implemented using an adapting scheme and minimum distance as optimization criterion, which is more suitable for weak edges detection. All methods are applied to glaucomatic retinal images with the purpose of segmenting the optical disk. The methods are compared in terms of segmentation accuracy and speed, as these are derived from cross-correlation coefficients between real and algorithm extracted contours and segmentation time, respectively. As a result, the method of self-affine mapping system presents adequate segmentation time and segmentation accuracy, and significant independence from initialization.

Anions mediate ligand binding in Adineta vaga glutamate receptor ion channels.

PubMed

Lomash, Suvendu; Chittori, Sagar; Brown, Patrick; Mayer, Mark L

2013-03-05

AvGluR1, a glutamate receptor ion channel from the primitive eukaryote Adineta vaga, is activated by alanine, cysteine, methionine, and phenylalanine, which produce lectin-sensitive desensitizing responses like those to glutamate, aspartate, and serine. AvGluR1 LBD crystal structures reveal an unusual scheme for binding dissimilar ligands that may be utilized by distantly related odorant/chemosensory receptors. Arginine residues in domain 2 coordinate the γ-carboxyl group of glutamate, whereas in the alanine, methionine, and serine complexes a chloride ion acts as a surrogate ligand, replacing the γ-carboxyl group. Removal of Cl(-) lowers affinity for these ligands but not for glutamate or aspartate nor for phenylalanine, which occludes the anion binding site and binds with low affinity. AvGluR1 LBD crystal structures and sedimentation analysis also provide insights into the evolutionary link between prokaryotic and eukaryotic iGluRs and reveal features unique to both classes, emphasizing the need for additional structure-based studies on iGluR-ligand interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Insight into the Meligethes aeneus voltage-sensitive sodium channel structure and an attempt to select the best pyrethroid ligands.

PubMed

Obrępalska-Stęplowska, Aleksandra; Czerwoniec, Anna; Wieczorek, Przemysław; Wrzesińska, Barbara

2016-01-01

The voltage-sensitive sodium channel (VSSC) is a target for the pharmacological action of pyrethroids which are used in controlling pests, including those of agricultural importance. Among these is the pollen beetle (Meligethes aeneus F.) - the most serious pest of Brassica napus. Owing to the heavy use of pyrethroids, a widespread build-up of resistance has occurred. The main cause of pyrethroid insensitivity in M. aeneus is considered to be an increased oxidative metabolism; however, the additional mechanism of resistance associated with mutations in the VSSC might contribute to this phenomenon. We generated a VSSC 3D model to study the docking affinities of pyrethroids to their target site within the channel. Our goal was to identify the pyrethroids for which docking affinity scores were high and not affected by potential mutations in the VSSC. We found that the docking scores of cypermethrin are hardly influenced by the appearance of point mutations. Additionally, tau-fluvalinate, deltamethrin and bifenthrin are VSSC ligands with high affinity scores. Our docking models suggest that point mutations in the VSSC binding pocket might affect the stability of ligand interactions and change the pattern of ligand docking locations, which might have a potential effect on VSSC gating properties. © 2015 Society of Chemical Industry.

White Matter Hyperintensities Improve Ischemic Stroke Recurrence Prediction.

PubMed

Andersen, Søren Due; Larsen, Torben Bjerregaard; Gorst-Rasmussen, Anders; Yavarian, Yousef; Lip, Gregory Y H; Bach, Flemming W

2017-01-01

Nearly one in 5 patients with ischemic stroke will invariably experience a second stroke within 5 years. Stroke risk stratification schemes based solely on clinical variables perform only modestly in non-atrial fibrillation (AF) patients and improvement of these schemes will enhance their clinical utility. Cerebral white matter hyperintensities are associated with an increased risk of incident ischemic stroke in the general population, whereas their association with the risk of ischemic stroke recurrence is more ambiguous. In a non-AF stroke cohort, we investigated the association between cerebral white matter hyperintensities and the risk of recurrent ischemic stroke, and we evaluated the predictive performance of the CHA2DS2VASc score and the Essen Stroke Risk Score (clinical scores) when augmented with information on white matter hyperintensities. In a registry-based, observational cohort study, we included 832 patients (mean age 59.6 (SD 13.9); 42.0% females) with incident ischemic stroke and no AF. We assessed the severity of white matter hyperintensities using MRI. Hazard ratios stratified by the white matter hyperintensities score and adjusted for the components of the CHA2DS2VASc score were calculated based on the Cox proportional hazards analysis. Recalibrated clinical scores were calculated by adding one point to the score for the presence of moderate to severe white matter hyperintensities. The discriminatory performance of the scores was assessed with the C-statistic. White matter hyperintensities were significantly associated with the risk of recurrent ischemic stroke after adjusting for clinical risk factors. The hazard ratios ranged from 1.65 (95% CI 0.70-3.86) for mild changes to 5.28 (95% CI 1.98-14.07) for the most severe changes. C-statistics for the prediction of recurrent ischemic stroke were 0.59 (95% CI 0.51-0.65) for the CHA2DS2VASc score and 0.60 (95% CI 0.53-0.68) for the Essen Stroke Risk Score. The recalibrated clinical scores showed improved C-statistics: the recalibrated CHA2DS2VASc score 0.62 (95% CI 0.54-0.70; p = 0.024) and the recalibrated Essen Stroke Risk Score 0.63 (95% CI 0.56-0.71; p = 0.031). C-statistics of the white matter hyperintensities score were 0.62 (95% CI 0.52-0.68) to 0.65 (95% CI 0.58-0.73). An increasing burden of white matter hyperintensities was independently associated with recurrent ischemic stroke in a cohort of non-AF ischemic stroke patients. Recalibration of the CHA2DS2VASc score and the Essen Stroke Risk Score with one point for the presence of moderate to severe white matter hyperintensities led to improved discriminatory performance in ischemic stroke recurrence prediction. Risk scores based on white matter hyperintensities alone were at least as accurate as the established clinical risk scores in the prediction of ischemic stroke recurrence. © 2016 S. Karger AG, Basel.

Proton affinity and enthalpy of formation of formaldehyde

NASA Astrophysics Data System (ADS)

Czakó, Gábor; Nagy, Balázs; Tasi, Gyula; Somogyi, Árpád; Šimunek, Ján; Noga, Jozef; Braams, Bastiaan J.; Bowman, Joel M.; Császár; , Attila G.

The proton affinity and the enthalpy of formation of the prototypical carbonyl, formaldehyde, have been determined by the first-principles composite focal-point analysis (FPA) approach. The electronic structure computations employed the all-electron coupled-cluster method with up to single, double, triple, quadruple, and even pentuple excitations. In these computations the aug-cc-p(C)VXZ [X = 2(D), 3(T), 4(Q), 5, and 6] correlation-consistent Gaussian basis sets for C and O were used in conjunction with the corresponding aug-cc-pVXZ (X = 2-6) sets for H. The basis set limit values have been confirmed via explicitly correlated computations. Our FPA study supersedes previous computational work for the proton affinity and to some extent the enthalpy of formation of formaldehyde by accounting for (a) electron correlation beyond the "gold standard" CCSD(T) level; (b) the non-additivity of core electron correlation effects; (c) scalar relativity; (d) diagonal Born-Oppenheimer corrections computed at a correlated level; (e) anharmonicity of zero-point vibrational energies, based on global potential energy surfaces and variational vibrational computations; and (f) thermal corrections to enthalpies by direct summation over rovibrational energy levels. Our final proton affinities at 298.15 (0.0) K are ΔpaHo (H2CO) = 711.02 (704.98) ± 0.39 kJ mol-1. Our final enthalpies of formation at 298.15 (0.0) K are ΔfHo (H2CO) = -109.23 (-105.42) ± 0.33 kJ mol-1. The latter values are based on the enthalpy of the H2 + CO → H2CO reaction but supported by two further reaction schemes, H2O + C → H2CO and 2H + C + O → H2CO. These values, especially ΔpaHo (H2CO), have better accuracy and considerably lower uncertainty than the best previous recommendations and thus should be employed in future studies.

Probing the binding affinity of amyloids to reduce toxicity of oligomers in diabetes

PubMed Central

Smaoui, Mohamed Raef; Orland, Henri; Waldispühl, Jérôme

2015-01-01

Motivation: Amyloids play a role in the degradation of β-cells in diabetes patients. In particular, short amyloid oligomers inject themselves into the membranes of these cells and create pores that disrupt the strictly controlled flow of ions through the membranes. This leads to cell death. Getting rid of the short oligomers either by a deconstruction process or by elongating them into longer fibrils will reduce this toxicity and allow the β-cells to live longer. Results: We develop a computational method to probe the binding affinity of amyloid structures and produce an amylin analog that binds to oligomers and extends their length. The binding and extension lower toxicity and β-cell death. The amylin analog is designed through a parsimonious selection of mutations and is to be administered with the pramlintide drug, but not to interact with it. The mutations (T9K L12K S28H T30K) produce a stable native structure, strong binding affinity to oligomers, and long fibrils. We present an extended mathematical model for the insulin–glucose relationship and demonstrate how affecting the concentration of oligomers with such analog is strictly coupled with insulin release and β-cell fitness. Availability and implementation: SEMBA, the tool to probe the binding affinity of amyloid proteins and generate the binding affinity scoring matrices and R-scores is available at: http://amyloid.cs.mcgill.ca Contact: jeromew@cs.mcgill.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25777526

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection.

PubMed

Zhuang, Xiahai; Bai, Wenjia; Song, Jingjing; Zhan, Songhua; Qian, Xiaohua; Shi, Wenzhe; Lian, Yanyun; Rueckert, Daniel

2015-07-01

Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors' proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.

Selecting registration schemes in case of interstitial lung disease follow-up in CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vlachopoulos, Georgios; Korfiatis, Panayiotis; Skiadopoulos, Spyros

Purpose: Primary goal of this study is to select optimal registration schemes in the framework of interstitial lung disease (ILD) follow-up analysis in CT. Methods: A set of 128 multiresolution schemes composed of multiresolution nonrigid and combinations of rigid and nonrigid registration schemes are evaluated, utilizing ten artificially warped ILD follow-up volumes, originating from ten clinical volumetric CT scans of ILD affected patients, to select candidate optimal schemes. Specifically, all combinations of four transformation models (three rigid: rigid, similarity, affine and one nonrigid: third order B-spline), four cost functions (sum-of-square distances, normalized correlation coefficient, mutual information, and normalized mutual information),more » four gradient descent optimizers (standard, regular step, adaptive stochastic, and finite difference), and two types of pyramids (recursive and Gaussian-smoothing) were considered. The selection process involves two stages. The first stage involves identification of schemes with deformation field singularities, according to the determinant of the Jacobian matrix. In the second stage, evaluation methodology is based on distance between corresponding landmark points in both normal lung parenchyma (NLP) and ILD affected regions. Statistical analysis was performed in order to select near optimal registration schemes per evaluation metric. Performance of the candidate registration schemes was verified on a case sample of ten clinical follow-up CT scans to obtain the selected registration schemes. Results: By considering near optimal schemes common to all ranking lists, 16 out of 128 registration schemes were initially selected. These schemes obtained submillimeter registration accuracies in terms of average distance errors 0.18 ± 0.01 mm for NLP and 0.20 ± 0.01 mm for ILD, in case of artificially generated follow-up data. Registration accuracy in terms of average distance error in clinical follow-up data was in the range of 1.985–2.156 mm and 1.966–2.234 mm, for NLP and ILD affected regions, respectively, excluding schemes with statistically significant lower performance (Wilcoxon signed-ranks test, p < 0.05), resulting in 13 finally selected registration schemes. Conclusions: Selected registration schemes in case of ILD CT follow-up analysis indicate the significance of adaptive stochastic gradient descent optimizer, as well as the importance of combined rigid and nonrigid schemes providing high accuracy and time efficiency. The selected optimal deformable registration schemes are equivalent in terms of their accuracy and thus compatible in terms of their clinical outcome.« less

Erratum: Development, appraisal, validation and implementation of a consensus protocol for the assessment of cerebral amyloid angiopathy in post-mortem brain tissue.

PubMed

Love, Seth; Chalmers, Katy; Ince, Paul; Esiri, Margaret; Attems, Johannes; Kalaria, Raj; Jellinger, Kurt; Yamada, Masahito; McCarron, Mark; Minett, Thais; Matthews, Fiona; Greenberg, Steven; Mann, David; Kehoe, Patrick Gavin

2015-01-01

In a collaboration involving 11 groups with research interests in cerebral amyloid angiopathy (CAA), we used a two-stage process to develop and in turn validate a new consensus protocol and scoring scheme for the assessment of CAA and associated vasculopathic abnormalities in post-mortem brain tissue. Stage one used an iterative Delphi-style survey to develop the consensus protocol. The resultant scoring scheme was tested on a series of digital images and paraffin sections that were circulated blind to a number of scorers. The scoring scheme and choice of staining methods were refined by open-forum discussion. The agreed protocol scored parenchymal and meningeal CAA on a 0-3 scale, capillary CAA as present/absent and vasculopathy on 0-2 scale, in the 4 cortical lobes that were scored separately. A further assessment involving three centres was then undertaken. Neuropathologists in three centres (Bristol, Oxford and Sheffield) independently scored sections from 75 cases (25 from each centre) and high inter-rater reliability was demonstrated. Stage two used the results of the three-centre assessment to validate the protocol by investigating previously described associations between APOE genotype (previously determined), and both CAA and vasculopathy. Association of capillary CAA with or without arteriolar CAA with APOE ε4 was confirmed. However APOE ε2 was also found to be a strong risk factor for the development of CAA, not only in AD but also in elderly non-demented controls. Further validation of this protocol and scoring scheme is encouraged, to aid its wider adoption to facilitate collaborative and replication studies of CAA.[This corrects the article on p. 19 in vol. 3, PMID: 24754000.].

Development, appraisal, validation and implementation of a consensus protocol for the assessment of cerebral amyloid angiopathy in post-mortem brain tissue

PubMed Central

Love, Seth; Chalmers, Katy; Ince, Paul; Esiri, Margaret; Attems, Johannes; Kalaria, Raj; Jellinger, Kurt; Yamada, Masahito; McCarron, Mark; Minett, Thais; Matthews, Fiona; Greenberg, Steven; Mann, David; Kehoe, Patrick Gavin

2015-01-01

In a collaboration involving 11 groups with research interests in cerebral amyloid angiopathy (CAA), we used a two-stage process to develop and in turn validate a new consensus protocol and scoring scheme for the assessment of CAA and associated vasculopathic abnormalities in post-mortem brain tissue. Stage one used an iterative Delphi-style survey to develop the consensus protocol. The resultant scoring scheme was tested on a series of digital images and paraffin sections that were circulated blind to a number of scorers. The scoring scheme and choice of staining methods were refined by open-forum discussion. The agreed protocol scored parenchymal and meningeal CAA on a 0-3 scale, capillary CAA as present/absent and vasculopathy on 0-2 scale, in the 4 cortical lobes that were scored separately. A further assessment involving three centres was then undertaken. Neuropathologists in three centres (Bristol, Oxford and Sheffield) independently scored sections from 75 cases (25 from each centre) and high inter-rater reliability was demonstrated. Stage two used the results of the three-centre assessment to validate the protocol by investigating previously described associations between APOE genotype (previously determined), and both CAA and vasculopathy. Association of capillary CAA with or without arteriolar CAA with APOE ε4 was confirmed. However APOE ε2 was also found to be a strong risk factor for the development of CAA, not only in AD but also in elderly non-demented controls. Further validation of this protocol and scoring scheme is encouraged, to aid its wider adoption to facilitate collaborative and replication studies of CAA. PMID:26807344

Development, appraisal, validation and implementation of a consensus protocol for the assessment of cerebral amyloid angiopathy in post-mortem brain tissue

PubMed Central

Love, Seth; Chalmers, Katy; Ince, Paul; Esiri, Margaret; Attems, Johannes; Jellinger, Kurt; Yamada, Masahito; McCarron, Mark; Minett, Thais; Matthews, Fiona; Greenberg, Steven; Mann, David; Kehoe, Patrick Gavin

2014-01-01

In a collaboration involving 11 groups with research interests in cerebral amyloid angiopathy (CAA), we used a two-stage process to develop and in turn validate a new consensus protocol and scoring scheme for the assessment of CAA and associated vasculopathic abnormalities in post-mortem brain tissue. Stage one used an iterative Delphi-style survey to develop the consensus protocol. The resultant scoring scheme was tested on a series of digital images and paraffin sections that were circulated blind to a number of scorers. The scoring scheme and choice of staining methods were refined by open-forum discussion. The agreed protocol scored parenchymal and meningeal CAA on a 0-3 scale, capillary CAA as present/absent and vasculopathy on 0-2 scale, in the 4 cortical lobes that were scored separately. A further assessment involving three centres was then undertaken. Neuropathologists in three centres (Bristol, Oxford and Sheffield) independently scored sections from 75 cases (25 from each centre) and high inter-rater reliability was demonstrated. Stage two used the results of the three-centre assessment to validate the protocol by investigating previously described associations between APOE genotype (previously determined), and both CAA and vasculopathy. Association of capillary CAA with or without arteriolar CAA with APOE ε4 was confirmed. However APOE ε2 was also found to be a strong risk factor for the development of CAA, not only in AD but also in elderly non-demented controls. Further validation of this protocol and scoring scheme is encouraged, to aid its wider adoption to facilitate collaborative and replication studies of CAA. PMID:24754000

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Recursive algorithms for bias and gain nonuniformity correction in infrared videos.

PubMed

Pipa, Daniel R; da Silva, Eduardo A B; Pagliari, Carla L; Diniz, Paulo S R

2012-12-01

Infrared focal-plane array (IRFPA) detectors suffer from fixed-pattern noise (FPN) that degrades image quality, which is also known as spatial nonuniformity. FPN is still a serious problem, despite recent advances in IRFPA technology. This paper proposes new scene-based correction algorithms for continuous compensation of bias and gain nonuniformity in FPA sensors. The proposed schemes use recursive least-square and affine projection techniques that jointly compensate for both the bias and gain of each image pixel, presenting rapid convergence and robustness to noise. The synthetic and real IRFPA videos experimentally show that the proposed solutions are competitive with the state-of-the-art in FPN reduction, by presenting recovered images with higher fidelity.

A robust and hierarchical approach for the automatic co-registration of intensity and visible images

NASA Astrophysics Data System (ADS)

González-Aguilera, Diego; Rodríguez-Gonzálvez, Pablo; Hernández-López, David; Luis Lerma, José

2012-09-01

This paper presents a new robust approach to integrate intensity and visible images which have been acquired with a terrestrial laser scanner and a calibrated digital camera, respectively. In particular, an automatic and hierarchical method for the co-registration of both sensors is developed. The approach integrates several existing solutions to improve the performance of the co-registration between range-based and visible images: the Affine Scale-Invariant Feature Transform (A-SIFT), the epipolar geometry, the collinearity equations, the Groebner basis solution and the RANdom SAmple Consensus (RANSAC), integrating a voting scheme. The approach presented herein improves the existing co-registration approaches in automation, robustness, reliability and accuracy.

The implementation of reverse Kessler warm rain scheme for radar reflectivity assimilation using a nudging approach in New Zealand

NASA Astrophysics Data System (ADS)

Zhang, Sijin; Austin, Geoff; Sutherland-Stacey, Luke

2014-05-01

Reverse Kessler warm rain processes were implemented within the Weather Research and Forecasting Model (WRF) and coupled with a Newtonian relaxation, or nudging technique designed to improve quantitative precipitation forecasting (QPF) in New Zealand by making use of observed radar reflectivity and modest computing facilities. One of the reasons for developing such a scheme, rather than using 4D-Var for example, is that radar VAR scheme in general, and 4D-Var in particular, requires computational resources beyond the capability of most university groups and indeed some national forecasting centres of small countries like New Zealand. The new scheme adjusts the model water vapor mixing ratio profiles based on observed reflectivity at each time step within an assimilation time window. The whole scheme can be divided into following steps: (i) The radar reflectivity is firstly converted to rain water, and (ii) then the rain water is used to derive cloud water content according to the reverse Kessler scheme; (iii) The cloud water content associated water vapor mixing ratio is then calculated based on the saturation adjustment processes; (iv) Finally the adjusted water vapor is nudged into the model and the model background is updated. 13 rainfall cases which occurred in the summer of 2011/2012 in New Zealand were used to evaluate the new scheme, different forecast scores were calculated and showed that the new scheme was able to improve precipitation forecasts on average up to around 7 hours ahead depending on different verification thresholds.

Band Alignment and Charge Transfer in Complex Oxide Interfaces

NASA Astrophysics Data System (ADS)

Zhong, Zhicheng; Hansmann, Philipp

2017-01-01

The synthesis of transition metal heterostructures is currently one of the most vivid fields in the design of novel functional materials. In this paper, we propose a simple scheme to predict band alignment and charge transfer in complex oxide interfaces. For semiconductor heterostructures, band-alignment rules like the well-known Anderson or Schottky-Mott rule are based on comparison of the work function or electron affinity of the bulk components. This scheme breaks down for oxides because of the invalidity of a single work-function approximation as recently shown in [Phys. Rev. B 93, 235116 (2016), 10.1103/PhysRevB.93.235116; Adv. Funct. Mater. 26, 5471 (2016), 10.1002/adfm.201600243]. Here, we propose a new scheme that is built on a continuity condition of valence states originating in the compounds' shared network of oxygen. It allows for the prediction of sign and relative amplitude of the intrinsic charge transfer, taking as input only information about the bulk properties of the components. We support our claims by numerical density functional theory simulations as well as (where available) experimental evidence. Specific applications include (i) controlled doping of SrTiO3 layers with the use of 4 d and 5 d transition metal oxides and (ii) the control of magnetic ordering in manganites through tuned charge transfer.

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

Radifar, Muhammad; Yuniarti, Nunung; Istyastono, Enade Perdana

2013-01-01

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). PyPLIF is freely available at http://code.google.com/p/pyplif.

Design and synthesis of N-(3,3-diphenylpropenyl)alkanamides as a novel class of high-affinity MT2-selective melatonin receptor ligands.

PubMed

Bedini, Annalida; Spadoni, Gilberto; Gatti, Giuseppe; Lucarini, Simone; Tarzia, Giorgio; Rivara, Silvia; Lorenzi, Simone; Lodola, Alessio; Mor, Marco; Lucini, Valeria; Pannacci, Marilou; Scaglione, Francesco

2006-12-14

A novel series of melatonin receptor ligands was discovered by opening the cyclic scaffolds of known classes of high affinity melatonin receptor antagonists, while retaining the pharmacophore elements postulated by previously described 3D-QSAR and receptor models. Compounds belonging to the classes of 2,3- and [3,3-diphenylprop(en)yl]alkanamides and of o- or [(m-benzyl)phenyl]ethyl-alkanamides were synthesized and tested on MT(1) and MT(2) receptors. The class of 3,3-diphenyl-propenyl-alkanamides was the most interesting one, with compounds having MT(2) receptor affinity similar to that of MLT, remarkable MT(2) selectivity, and partial agonist or antagonist behavior. In particular, the (E)-m-methoxy cyclobutanecarboxamido derivative 18f and the di-(m-methoxy) acetamido one, 18g, have sub-nM affinity for the MT(2) subtype, with more than 100-fold selectivity over MT(1), 18f being an antagonist and 18g a partial agonist on GTPgammaS test. Docking of 18g into a previously developed MT(2) receptor model showed a binding scheme consistent with that of other antagonists. The MT(2) expected binding affinities of the new compounds were calculated by a previously developed 3D-QSAR CoMFA model, giving satisfactory predictions.

Evaluation of an Inverse Molecular Design Algorithm in a Model Binding Site

PubMed Central

Huggins, David J.; Altman, Michael D.; Tidor, Bruce

2008-01-01

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors [M. D. Altman et al. J. Am. Chem. Soc. 130: 6099–6013, 2008]. Here we have evaluated the new method using the well studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from non-binders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the non-binders. PMID:18831031

Evaluation of an inverse molecular design algorithm in a model binding site.

PubMed

Huggins, David J; Altman, Michael D; Tidor, Bruce

2009-04-01

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors (Altman et al., J Am Chem Soc 2008;130:6099-6013). Here we have evaluated the new method using the well-studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from nonbinders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions, and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the nonbinders. (c) 2008 Wiley-Liss, Inc.

Associations of medical student empathy with clinical competence.

PubMed

Casas, Rachel S; Xuan, Ziming; Jackson, Angela H; Stanfield, Lorraine E; Harvey, Nanette C; Chen, Daniel C

2017-04-01

Empathy is a crucial skill for medical students that can be difficult to evaluate. We examined if self-reported empathy in medical students was associated with clinical competence. This study combined cross-sectional data from four consecutive years of medical students (N=590) from the Boston University School of Medicine. We used regression analysis to evaluate if self-reported empathy (Jefferson Scale of Physician Empathy (JSPE)) predicted scores in clinical clerkships, United States Medical Licensing Examinations, and OBJECTIVE: Structured Clinical Examinations (OSCEs). We separately analyzed overall and OSCE communication scores based on interpersonal skills reported by standardized patients. We controlled for age, gender, debt, and specialty affinity. JSPE scores of medical students were positively associated with OSCE communication scores, and remained significant when controlling for demographics. We found that JSPE score was also predictive of overall OSCE scores, but this relationship was confounded by gender and age. JSPE scores were associated with performance in the Pediatrics clerkship, but not other clerkships or standardized tests. JSPE scores were positively associated with OSCE communication scores in medical students. This study supports that self-reported empathy may predict OSCE performance, but further research is needed to examine differences by gender and age. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reinforce: An Ensemble Approach for Inferring PPI Network from AP-MS Data.

PubMed

Tian, Bo; Duan, Qiong; Zhao, Can; Teng, Ben; He, Zengyou

2017-05-17

Affinity Purification-Mass Spectrometry (AP-MS) is one of the most important technologies for constructing protein-protein interaction (PPI) networks. In this paper, we propose an ensemble method, Reinforce, for inferring PPI network from AP-MS data set. The new algorithm named Reinforce is based on rank aggregation and false discovery rate control. Under the null hypothesis that the interaction scores from different scoring methods are randomly generated, Reinforce follows three steps to integrate multiple ranking results from different algorithms or different data sets. The experimental results show that Reinforce can get more stable and accurate inference results than existing algorithms. The source codes of Reinforce and data sets used in the experiments are available at: https://sourceforge.net/projects/reinforce/.

Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.

PubMed

Martiny, Virginie Y; Martz, François; Selwa, Edithe; Iorga, Bogdan I

2016-06-27

The 2014 CSAR Benchmark Exercise was focused on three protein targets: coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.

Temporal Hierarchy of Gene Expression Mediated by Transcription Factor Binding Affinity and Activation Dynamics

PubMed Central

Gao, Rong

2015-01-01

ABSTRACT Understanding cellular responses to environmental stimuli requires not only the knowledge of specific regulatory components but also the quantitative characterization of the magnitude and timing of regulatory events. The two-component system is one of the major prokaryotic signaling schemes and is the focus of extensive interest in quantitative modeling and investigation of signaling dynamics. Here we report how the binding affinity of the PhoB two-component response regulator (RR) to target promoters impacts the level and timing of expression of PhoB-regulated genes. Information content has often been used to assess the degree of conservation for transcription factor (TF)-binding sites. We show that increasing the information content of PhoB-binding sites in designed phoA promoters increased the binding affinity and that the binding affinity and concentration of phosphorylated PhoB (PhoB~P) together dictate the level and timing of expression of phoA promoter variants. For various PhoB-regulated promoters with distinct promoter architectures, expression levels appear not to be correlated with TF-binding affinities, in contrast to the intuitive and oversimplified assumption that promoters with higher affinity for a TF tend to have higher expression levels. However, the expression timing of the core set of PhoB-regulated genes correlates well with the binding affinity of PhoB~P to individual promoters and the temporal hierarchy of gene expression appears to be related to the function of gene products during the phosphate starvation response. Modulation of the information content and binding affinity of TF-binding sites may be a common strategy for temporal programming of the expression profile of RR-regulated genes. PMID:26015501

Coupling of G Proteins to Reconstituted Monomers and Tetramers of the M2 Muscarinic Receptor*

PubMed Central

Redka, Dar'ya S.; Morizumi, Takefumi; Elmslie, Gwendolynne; Paranthaman, Pranavan; Shivnaraine, Rabindra V.; Ellis, John; Ernst, Oliver P.; Wells, James W.

2014-01-01

G protein-coupled receptors can be reconstituted as monomers in nanodiscs and as tetramers in liposomes. When reconstituted with G proteins, both forms enable an allosteric interaction between agonists and guanylyl nucleotides. Both forms, therefore, are candidates for the complex that controls signaling at the level of the receptor. To identify the biologically relevant form, reconstituted monomers and tetramers of the purified M2 muscarinic receptor were compared with muscarinic receptors in sarcolemmal membranes for the effect of guanosine 5′-[β,γ-imido]triphosphate (GMP-PNP) on the inhibition of N-[3H]methylscopolamine by the agonist oxotremorine-M. With monomers, a stepwise increase in the concentration of GMP-PNP effected a lateral, rightward shift in the semilogarithmic binding profile (i.e. a progressive decrease in the apparent affinity of oxotremorine-M). With tetramers and receptors in sarcolemmal membranes, GMP-PNP effected a vertical, upward shift (i.e. an apparent redistribution of sites from a state of high affinity to one of low affinity with no change in affinity per se). The data were analyzed in terms of a mechanistic scheme based on a ligand-regulated equilibrium between uncoupled and G protein-coupled receptors (the “ternary complex model”). The model predicts a rightward shift in the presence of GMP-PNP and could not account for the effects at tetramers in vesicles or receptors in sarcolemmal membranes. Monomers present a special case of the model in which agonists and guanylyl nucleotides interact within a complex that is both constitutive and stable. The results favor oligomers of the M2 receptor over monomers as the biologically relevant state for coupling to G proteins. PMID:25023280

Coupling of g proteins to reconstituted monomers and tetramers of the M2 muscarinic receptor.

PubMed

Redka, Dar'ya S; Morizumi, Takefumi; Elmslie, Gwendolynne; Paranthaman, Pranavan; Shivnaraine, Rabindra V; Ellis, John; Ernst, Oliver P; Wells, James W

2014-08-29

G protein-coupled receptors can be reconstituted as monomers in nanodiscs and as tetramers in liposomes. When reconstituted with G proteins, both forms enable an allosteric interaction between agonists and guanylyl nucleotides. Both forms, therefore, are candidates for the complex that controls signaling at the level of the receptor. To identify the biologically relevant form, reconstituted monomers and tetramers of the purified M2 muscarinic receptor were compared with muscarinic receptors in sarcolemmal membranes for the effect of guanosine 5'-[β,γ-imido]triphosphate (GMP-PNP) on the inhibition of N-[(3)H]methylscopolamine by the agonist oxotremorine-M. With monomers, a stepwise increase in the concentration of GMP-PNP effected a lateral, rightward shift in the semilogarithmic binding profile (i.e. a progressive decrease in the apparent affinity of oxotremorine-M). With tetramers and receptors in sarcolemmal membranes, GMP-PNP effected a vertical, upward shift (i.e. an apparent redistribution of sites from a state of high affinity to one of low affinity with no change in affinity per se). The data were analyzed in terms of a mechanistic scheme based on a ligand-regulated equilibrium between uncoupled and G protein-coupled receptors (the "ternary complex model"). The model predicts a rightward shift in the presence of GMP-PNP and could not account for the effects at tetramers in vesicles or receptors in sarcolemmal membranes. Monomers present a special case of the model in which agonists and guanylyl nucleotides interact within a complex that is both constitutive and stable. The results favor oligomers of the M2 receptor over monomers as the biologically relevant state for coupling to G proteins. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Assessing the Reliability and Use of the Expository Scoring Scheme as a Measure of Developmental Change in Monolingual English and Bilingual French/English Children

ERIC Educational Resources Information Center

Bird, Elizabeth Kay-Raining; Joshi, Nila; Cleave, Patricia L.

2016-01-01

Purpose: The Expository Scoring Scheme (ESS) is designed to analyze the macrostructure of descriptions of a favorite game or sport. This pilot study examined inter- and intrarater reliability of the ESS and use of the scale to capture developmental change in elementary school children. Method: Twenty-four children in 2 language groups (monolingual…

Electronic structure probed with positronium: Theoretical viewpoint

NASA Astrophysics Data System (ADS)

Kuriplach, Jan; Barbiellini, Bernardo

2018-05-01

We inspect carefully how the positronium can be used to study the electronic structure of materials. Recent combined experimental and computational study [A.C.L. Jones et al., Phys. Rev. Lett. 117, 216402 (2016)] has shown that the positronium affinity can be used to benchmark the exchange-correlation approximations in copper. Here we investigate whether an improvement can be achieved by increasing the numerical precision of calculations and by employing the strongly constrained and appropriately normed (SCAN) scheme, and extend the study to other selected systems like aluminum and high entropy alloys. From the methodological viewpoint, the computations of the positronium affinity are further refined and an alternative way of determining the electron chemical potential using charged supercells is examined.

Selection of specific interactors from phage display library based on sea lamprey variable lymphocyte receptor sequences.

PubMed

Wezner-Ptasinska, Magdalena; Otlewski, Jacek

2015-12-01

Variable lymphocyte receptors (VLRs) are non-immunoglobulin components of adaptive immunity in jawless vertebrates. These proteins composed of leucine-rich repeat modules offer some advantages over antibodies in target binding and therefore are attractive candidates for biotechnological applications. In this paper we report the design and characterization of a phage display library based on a previously proposed dVLR scaffold containing six LRR modules [Wezner-Ptasinska et al., 2011]. Our library was designed based on a consensus approach in which the randomization scheme reflects the frequencies of amino acids naturally occurring in respective positions responsible for antigen recognition. We demonstrate general applicability of the scaffold by selecting dVLRs specific for lysozyme and S100A7 protein with KD values in the micromolar range. The dVLR library could be used as a convenient alternative to antibodies for effective isolation of high affinity binders.

Data-based fault-tolerant control for affine nonlinear systems with actuator faults.

PubMed

Xie, Chun-Hua; Yang, Guang-Hong

2016-09-01

This paper investigates the fault-tolerant control (FTC) problem for unknown nonlinear systems with actuator faults including stuck, outage, bias and loss of effectiveness. The upper bounds of stuck faults, bias faults and loss of effectiveness faults are unknown. A new data-based FTC scheme is proposed. It consists of the online estimations of the bounds and a state-dependent function. The estimations are adjusted online to compensate automatically the actuator faults. The state-dependent function solved by using real system data helps to stabilize the system. Furthermore, all signals in the resulting closed-loop system are uniformly bounded and the states converge asymptotically to zero. Compared with the existing results, the proposed approach is data-based. Finally, two simulation examples are provided to show the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Life cycle and molecular phylogeny of the dinoflagellates Chytriodinium and Dissodinium, ectoparasites of copepod eggs.

PubMed

Gómez, Fernando; Moreira, David; López-García, Purificación

2009-11-01

The dinoflagellates Chytriodinium affine, C. roseum and Dissodinium pseudolunula are ectoparasites of crustacean eggs. Here, we present new observations regarding their life cycle based on coastal plankton samples and incubations and analyze their molecular phylogeny using the small subunit ribosomal RNA gene (SSU rDNA) as a marker. In contrast to the typical stages already documented for its life cycle, we observed that D. pseudolunula dinospores may exceptionally differentiate inside a globular cyst. Despite its parasitic life style, the cysts and dinospores of D. pseudolunula contain chlorophyll a. We obtained the first SSU rDNA sequences for the genera Chytriodinium (the type C. roseum and C. affine) and Dissodinium (D. pseudolunula). Classical taxonomical schemes have ascribed these genera to the order Blastodiniales. However, our SSU rDNA-based phylogenetic analysis shows that these ectoparasites form a clade in the Gymnodinium sensu stricto group, unarmored dinokaryotic dinoflagellates of the order Gymnodiniales. They branch in a subgroup composed of warnowiids, polykrikoids, the type of Gymnodinium, G. fuscum and G. aureolum. Although Chytriodinium and Dissodinium appear to be relatives based on SSU rDNA phylogeny, feeding and host specificity, their life cycles are substantially different. Based on these data we consider that the type of life cycle is a poor criterion for classification at the family level. We suggest that the morphology of the infective cell is probably the most reliable phenotypic characteristic to determine the systematic position of parasitic dinoflagellates.

A group electronegativity equalization scheme including external potential effects.

PubMed

Leyssens, Tom; Geerlings, Paul; Peeters, Daniel

2006-07-20

By calculating the electron affinity and ionization energy of different functional groups, CCSD electronegativity values are obtained, which implicitly account for the effect of the molecular environment. This latter is approximated using a chemically justified point charge model. On the basis of Sanderson's electronegativity equalization principle, this approach is shown to lead to reliable "group in molecule" electronegativities. Using a slight adjustment of the modeled environment and first-order principles, an electronegativity equalization scheme is obtained, which implicitly accounts for the major part of the external potential effect. This scheme can be applied in a predictive manner to estimate the charge transfer between two functional groups, without having to rely on cumbersome calibrations. A very satisfactory correlation is obtained between these charge transfers and those obtained from an ab initio calculation of the entire molecule.

Scoring Rubric Development: Validity and Reliability.

ERIC Educational Resources Information Center

Moskal, Barbara M.; Leydens, Jon A.

2000-01-01

Provides clear definitions of the terms "validity" and "reliability" in the context of developing scoring rubrics and illustrates these definitions through examples. Also clarifies how validity and reliability may be addressed in the development of scoring rubrics, defined as descriptive scoring schemes developed to guide the analysis of the…

PSSMHCpan: a novel PSSM-based software for predicting class I peptide-HLA binding affinity

PubMed Central

Liu, Geng; Li, Dongli; Li, Zhang; Qiu, Si; Li, Wenhui; Chao, Cheng-chi; Yang, Naibo; Li, Handong; Cheng, Zhen; Song, Xin; Cheng, Le; Zhang, Xiuqing; Wang, Jian; Yang, Huanming

2017-01-01

Abstract Predicting peptide binding affinity with human leukocyte antigen (HLA) is a crucial step in developing powerful antitumor vaccine for cancer immunotherapy. Currently available methods work quite well in predicting peptide binding affinity with HLA alleles such as HLA-A*0201, HLA-A*0101, and HLA-B*0702 in terms of sensitivity and specificity. However, quite a few types of HLA alleles that are present in the majority of human populations including HLA-A*0202, HLA-A*0203, HLA-A*6802, HLA-B*5101, HLA-B*5301, HLA-B*5401, and HLA-B*5701 still cannot be predicted with satisfactory accuracy using currently available methods. Furthermore, currently the most popularly used methods for predicting peptide binding affinity are inefficient in identifying neoantigens from a large quantity of whole genome and transcriptome sequencing data. Here we present a Position Specific Scoring Matrix (PSSM)-based software called PSSMHCpan to accurately and efficiently predict peptide binding affinity with a broad coverage of HLA class I alleles. We evaluated the performance of PSSMHCpan by analyzing 10-fold cross-validation on a training database containing 87 HLA alleles and obtained an average area under receiver operating characteristic curve (AUC) of 0.94 and accuracy (ACC) of 0.85. In an independent dataset (Peptide Database of Cancer Immunity) evaluation, PSSMHCpan is substantially better than the popularly used NetMHC-4.0, NetMHCpan-3.0, PickPocket, Nebula, and SMM with a sensitivity of 0.90, as compared to 0.74, 0.81, 0.77, 0.24, and 0.79. In addition, PSSMHCpan is more than 197 times faster than NetMHC-4.0, NetMHCpan-3.0, PickPocket, sNebula, and SMM when predicting neoantigens from 661 263 peptides from a breast tumor sample. Finally, we built a neoantigen prediction pipeline and identified 117 017 neoantigens from 467 cancer samples of various cancers from TCGA. PSSMHCpan is superior to the currently available methods in predicting peptide binding affinity with a broad coverage of HLA class I alleles. PMID:28327987

Market behavior and performance of different strategy evaluation schemes.

PubMed

Baek, Yongjoo; Lee, Sang Hoon; Jeong, Hawoong

2010-08-01

Strategy evaluation schemes are a crucial factor in any agent-based market model, as they determine the agents' strategy preferences and consequently their behavioral pattern. This study investigates how the strategy evaluation schemes adopted by agents affect their performance in conjunction with the market circumstances. We observe the performance of three strategy evaluation schemes, the history-dependent wealth game, the trend-opposing minority game, and the trend-following majority game, in a stock market where the price is exogenously determined. The price is either directly adopted from the real stock market indices or generated with a Markov chain of order ≤2 . Each scheme's success is quantified by average wealth accumulated by the traders equipped with the scheme. The wealth game, as it learns from the history, shows relatively good performance unless the market is highly unpredictable. The majority game is successful in a trendy market dominated by long periods of sustained price increase or decrease. On the other hand, the minority game is suitable for a market with persistent zigzag price patterns. We also discuss the consequence of implementing finite memory in the scoring processes of strategies. Our findings suggest under which market circumstances each evaluation scheme is appropriate for modeling the behavior of real market traders.

SAR studies on truxillic acid mono esters as a new class of antinociceptive agents targeting fatty acid binding proteins.

PubMed

Yan, Su; Elmes, Matthew W; Tong, Simon; Hu, Kongzhen; Awwa, Monaf; Teng, Gary Y H; Jing, Yunrong; Freitag, Matthew; Gan, Qianwen; Clement, Timothy; Wei, Longfei; Sweeney, Joseph M; Joseph, Olivia M; Che, Joyce; Carbonetti, Gregory S; Wang, Liqun; Bogdan, Diane M; Falcone, Jerome; Smietalo, Norbert; Zhou, Yuchen; Ralph, Brian; Hsu, Hao-Chi; Li, Huilin; Rizzo, Robert C; Deutsch, Dale G; Kaczocha, Martin; Ojima, Iwao

2018-05-24

Fatty acid binding proteins (FABPs) serve as critical modulators of endocannabinoid signaling by facilitating the intracellular transport of anandamide and whose inhibition potentiates anandamide signaling. Our previous work has identified a novel small-molecule FABP inhibitor, α-truxillic acid 1-naphthyl monoester (SB-FI-26, 3) that has shown efficacy as an antinociceptive and anti-inflammatory agent in rodent models. In the present work, we have performed an extensive SAR study on a series of 3-analogs as novel FABP inhibitors based on computer-aided inhibitor drug design and docking analysis, chemical synthesis and biological evaluations. The prediction of binding affinity of these analogs to target FABP3, 5 and 7 isoforms was performed using the AutoDock 4.2 program, using the recently determined co-crystal structures of 3 with FABP5 and FABP7. The compounds with high docking scores were synthesized and evaluated for their activities using a fluorescence displacement assay against FABP3, 5 and 7. During lead optimization, compound 3l emerged as a promising compound with the Ki value of 0.21 μM for FABP 5, 4-fold more potent than 3 (Ki, 0.81 μM). Nine compounds exhibit similar or better binding affinity than 3, including compounds 4b (Ki, 0.55 μM) and 4e (Ki, 0.68 μM). Twelve compounds are selective for FABP5 and 7 with >10 μM Ki values for FABP3, indicating a safe profile to avoid potential cardiotoxicity concerns. Compounds 4f, 4j and 4k showed excellent selectivity for FABP5 and would serve as other new lead compounds. Compound 3a possessed high affinity and high selectivity for FABP7. Compounds with moderate to high affinity for FABP5 displayed antinociceptive effects in mice while compounds with low FABP5 affinity lacked in vivo efficacy. In vivo pain model studies in mice revealed that exceeding hydrophobicity significantly affects the efficacy. Thus, among the compounds with high affinity to FABP5 in vitro, the compounds with moderate hydrophobicity were identified as promising new lead compounds for the next round of optimization, including compounds 4b and 4j. For select cases, computational analysis of the observed SAR, especially the selectivity of new inhibitors to particular FABP isoforms, by comparing docking poses, interaction map, and docking energy scores has provided useful insights. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

A hybrid deep learning approach to predict malignancy of breast lesions using mammograms

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Heidari, Morteza; Mirniaharikandehei, Seyedehnafiseh; Gong, Jing; Qian, Wei; Qiu, Yuchen; Zheng, Bin

2018-03-01

Applying deep learning technology to medical imaging informatics field has been recently attracting extensive research interest. However, the limited medical image dataset size often reduces performance and robustness of the deep learning based computer-aided detection and/or diagnosis (CAD) schemes. In attempt to address this technical challenge, this study aims to develop and evaluate a new hybrid deep learning based CAD approach to predict likelihood of a breast lesion detected on mammogram being malignant. In this approach, a deep Convolutional Neural Network (CNN) was firstly pre-trained using the ImageNet dataset and serve as a feature extractor. A pseudo-color Region of Interest (ROI) method was used to generate ROIs with RGB channels from the mammographic images as the input to the pre-trained deep network. The transferred CNN features from different layers of the CNN were then obtained and a linear support vector machine (SVM) was trained for the prediction task. By applying to a dataset involving 301 suspicious breast lesions and using a leave-one-case-out validation method, the areas under the ROC curves (AUC) = 0.762 and 0.792 using the traditional CAD scheme and the proposed deep learning based CAD scheme, respectively. An ensemble classifier that combines the classification scores generated by the two schemes yielded an improved AUC value of 0.813. The study results demonstrated feasibility and potentially improved performance of applying a new hybrid deep learning approach to develop CAD scheme using a relatively small dataset of medical images.

Heuristic reusable dynamic programming: efficient updates of local sequence alignment.

PubMed

Hong, Changjin; Tewfik, Ahmed H

2009-01-01

Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm.

Studies on molecular properties prediction and histamine H3 receptor affinities of novel ligands with uracil-based motifs.

PubMed

Lipani, Luca; Odadzic, Dalibor; Weizel, Lilia; Schwed, Johannes-Stephan; Sadek, Bassem; Stark, Holger

2014-10-30

The histamine H3 receptor (H3R) plays a role in cognitive and memory processes and is involved in different neurological disorders, including Alzheimer's disease, schizophrenia, and narcolepsy. Therefore, several hH3R antagonists/inverse agonists entered clinical phases for a broad spectrum of mainly centrally occurring diseases. However, many other promising candidates failed due to their pharmacokinetic profile, mostly because of their strong lipophilicity accompanied with low solubility. Analysis of previous potential H3R selective antagonists/inverse agonists, e.g. pitolisant, revealed promising results concerning physicochemical properties and drug-likeness. Herein, a series of new hH3R ligands 8-20 consisting of piperidin-1-yl or piperidin-1-yl-propoxyphenyl coupled to different uracil, thymine, and 5,6-dimethyluracil related moieties, were synthesized, evaluated on their binding properties at the hH3R and the estimation of different physicochemical and drug-likeness properties. Due to the coupling to various positions at pyrimidine-2,4-(1H,3H)-dione, affinity at hH3Rs and drug-likeness parameters have been improved. For instance, compound 9 showed in addition to high affinity at the hH3R (pKi (hH3R) = 8.14) clog S, clog P, LE, LipE, and drug-likeness score values of -4.36, 3.47, 0.34, 4.63, and 1.54, respectively. Also, the methyl substituted analog 17 (pKi (hH3R) = 8.15) revealed LE, LipE and drug-likeness score values of -3.29, 2.47, 0.49, 5.52, and 1.76, respectively. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme

NASA Astrophysics Data System (ADS)

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-08-01

The high false-positive recall rate is one of the major dilemmas that significantly reduce the efficacy of screening mammography, which harms a large fraction of women and increases healthcare cost. This study aims to investigate the feasibility of helping reduce false-positive recalls by developing a new computer-aided diagnosis (CAD) scheme based on the analysis of global mammographic texture and density features computed from four-view images. Our database includes full-field digital mammography (FFDM) images acquired from 1052 recalled women (669 positive for cancer and 383 benign). Each case has four images: two craniocaudal (CC) and two mediolateral oblique (MLO) views. Our CAD scheme first computed global texture features related to the mammographic density distribution on the segmented breast regions of four images. Second, the computed features were given to two artificial neural network (ANN) classifiers that were separately trained and tested in a ten-fold cross-validation scheme on CC and MLO view images, respectively. Finally, two ANN classification scores were combined using a new adaptive scoring fusion method that automatically determined the optimal weights to assign to both views. CAD performance was tested using the area under a receiver operating characteristic curve (AUC). The AUC = 0.793  ±  0.026 was obtained for this four-view CAD scheme, which was significantly higher at the 5% significance level than the AUCs achieved when using only CC (p = 0.025) or MLO (p = 0.0004) view images, respectively. This study demonstrates that a quantitative assessment of global mammographic image texture and density features could provide useful and/or supplementary information to classify between malignant and benign cases among the recalled cases, which may eventually help reduce the false-positive recall rate in screening mammography.

Physics-based enzyme design: predicting binding affinity and catalytic activity.

PubMed

Sirin, Sarah; Pearlman, David A; Sherman, Woody

2014-12-01

Computational enzyme design is an emerging field that has yielded promising success stories, but where numerous challenges remain. Accurate methods to rapidly evaluate possible enzyme design variants could provide significant value when combined with experimental efforts by reducing the number of variants needed to be synthesized and speeding the time to reach the desired endpoint of the design. To that end, extending our computational methods to model the fundamental physical-chemical principles that regulate activity in a protocol that is automated and accessible to a broad population of enzyme design researchers is essential. Here, we apply a physics-based implicit solvent MM-GBSA scoring approach to enzyme design and benchmark the computational predictions against experimentally determined activities. Specifically, we evaluate the ability of MM-GBSA to predict changes in affinity for a steroid binder protein, catalytic turnover for a Kemp eliminase, and catalytic activity for α-Gliadin peptidase variants. Using the enzyme design framework developed here, we accurately rank the most experimentally active enzyme variants, suggesting that this approach could provide enrichment of active variants in real-world enzyme design applications. © 2014 Wiley Periodicals, Inc.

The Weighting Is The Hardest Part: On The Behavior of the Likelihood Ratio Test and the Score Test Under a Data-Driven Weighting Scheme in Sequenced Samples

PubMed Central

Minică, Camelia C.; Genovese, Giulio; Hultman, Christina M.; Pool, René; Vink, Jacqueline M.; Neale, Michael C.; Dolan, Conor V.; Neale, Benjamin M.

2017-01-01

Sequence-based association studies are at a critical inflexion point with the increasing availability of exome-sequencing data. A popular test of association is the sequence kernel association test (SKAT). Weights are embedded within SKAT to reflect the hypothesized contribution of the variants to the trait variance. Because the true weights are generally unknown, and so are subject to misspecification, we examined the efficiency of a data-driven weighting scheme. We propose the use of a set of theoretically defensible weighting schemes, of which, we assume, the one that gives the largest test statistic is likely to capture best the allele frequency-functional effect relationship. We show that the use of alternative weights obviates the need to impose arbitrary frequency thresholds in sequence data association analyses. As both the score test and the likelihood ratio test (LRT) may be used in this context, and may differ in power, we characterize the behavior of both tests. We found that the two tests have equal power if the set of weights resembled the correct ones. However, if the weights are badly specified, the LRT shows superior power (due to its robustness to misspecification). With this data-driven weighting procedure the LRT detected significant signal in genes located in regions already confirmed as associated with schizophrenia – the PRRC2A (P=1.020E-06) and the VARS2 (P=2.383E-06) – in the Swedish schizophrenia case-control cohort of 11,040 individuals with exome-sequencing data. The score test is currently preferred for its computational efficiency and power. Indeed, assuming correct specification, in some circumstances the score test is the most powerful. However, LRT has the advantageous properties of being generally more robust and more powerful under weight misspecification. This is an important result given that, arguably, misspecified models are likely to be the rule rather than the exception in weighting-based approaches. PMID:28238293

Affinity-seeking, social loneliness, and social avoidance among Facebook users.

PubMed

Lemieux, Robert; Lajoie, Sean; Trainor, Nathan E

2013-04-01

This study explored the relations between use of the social networking site Facebook and scores on affinity-seeking, social loneliness, and social avoidance by 313 college students. Social loneliness and social avoidance, but not affinity-seeking, were positively and statistically significantly related to time spent using Facebook. The number of close Facebook friends was negatively and statistically significantly related to social loneliness and social avoidance. Women perceived Facebook as a more integral part of daily interactions than did men. 38% of the 283 Facebook members indicated their accounts contained information and/or a picture that could embarrass them, with men having significantly more embarrassing content than women. The findings are discussed within the context of social compensation.

Evaluation of a Picture-Based Test for the Assessment of Gelotophobia.

PubMed

Ruch, Willibald; Platt, Tracey; Bruntsch, Richard; Ďurka, Róbert

2017-01-01

This study examines whether coding open answers in a picture-based test, as to the extent they reflect the fear of being laughed at (i.e., gelotophobia), demonstrates sufficient validity to construct a semi-projective test for the assessment of gelotophobia. Previous findings indicate that cartoon stimuli depicting laughter situations (i.e., in the pilot version of the Picture-Geloph; Ruch et al., 2009) on average elicit fear-typical responses in gelotophobes stronger than in non-gelotophobes. The present study aims to (a) develop a standardized scoring procedure based on a coding scheme, and (b) examine the properties of the pilot version of the Picture-Geloph in order to select the most acceptable items for a standard form of the test. For Study 1, a sample of N = 126 adults, with scores evenly distributed across the gelotophobia spectrum, completed the pilot version of the Picture-Geloph by noting down what they assumed the protagonist in each of 20 cartoons would say or think. Furthermore, participants answered the GELOPH<15> (Ruch and Proyer, 2008), the established questionnaire for the subjective assessment of the fear of being laughed at. Agreement between two independent raters indicated that the developed coding scheme allows for objective and reliable scoring of the Picture-Geloph (mean of intraclass correlations = 0.66). Nine items met the criteria employed to identify the psychometrically most reliable and valid items. These items were unidimensional and internally consistent (Cronbach's alpha = 0.78). The total score of this selection (i.e., the Picture-Geloph<9>) discriminated significantly between non-fearful, slightly, markedly, and extremely fearful individuals; furthermore, it correlated sufficiently high ( r = 0.66; r c = 0.79 when corrected for reliability of both measures) with the GELOPH<15>. Cronbach's alpha (0.73) was largely comparable whereas the estimate of convergent validity was found to be lower in one ( r = 0.50; r c = 0.61; N = 103) of the two samples in Study 2. Combining all three samples ( N = 313) yielded a linear relationship between the self-report and the Picture-Geloph. With the Picture-Geloph<9> and the developed coding scheme, an unobtrusive and valid alternative instrument for the assessment of gelotophobia is provided. Possible applications are discussed.

Functionalized gold nanostars for label-free detection of PKA phosphorylation using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

He, Shuai; Kah, James C. Y.

2017-04-01

Protein phosphorylation controls fundamental biological processes. Dysregulation of protein kinase is associated with a series of human diseases including cancer. Protein kinase A (PKA) activity has been reported to serve as a potential prognostic marker for cancer. To this end, we developed a non-radioactive, rapid, cheap and robust scheme based on surface-enhanced Raman spectroscopy (SERS) for label-free detection of PKA phosphorylation using gold nanostars (AuNS) functionalized with BSA-kemptide. While bovine serum albumin (BSA) proteins stabilized the AuNS, kemptide, which is a high affinity substrate peptide specific for PKA, were phosphorylated in vitro to generate Raman signals that were identified by performing principal component analysis (PCA) on the acquired SERS spectra.

Theoretical study of the electron affinities of MF6 and MF - 6 (M=Cr, Mo, and W) using a model potential method

NASA Astrophysics Data System (ADS)

Sakai, Yoshiko; Miyoshi, Eisaku

1987-09-01

Electronic structures of MF6, MF-6, and MF2-6 (M=Cr, Mo, and W) were calculated using a model potential method in the Hartree-Fock-Roothaan scheme. Major relativistic effects were taken into account for the calculations on MoFq6 and WFq6 (q=0, -1, and -2). It is shown that the calculated electron affinities (EAs) are extremely high for all the MF6 molecules, and that the CrF-6 and MoF-6 anions also have positive EAs, whereas the WF-6 anion has a slightly negative EA. The behaviors of the EAs are interpreted with reference to the electronic structures of the MFq6 systems.

Sequential sampling: a novel method in farm animal welfare assessment.

PubMed

Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

2016-02-01

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

PubMed

Yang, Qinmin; Jagannathan, Sarangapani

2012-04-01

In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhuang, Xiahai, E-mail: zhuangxiahai@sjtu.edu.cn; Qian, Xiaohua; Bai, Wenjia

Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluatingmore » the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. Conclusions: The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.« less

Local alignment of two-base encoded DNA sequence

PubMed Central

Homer, Nils; Merriman, Barry; Nelson, Stanley F

2009-01-01

Background DNA sequence comparison is based on optimal local alignment of two sequences using a similarity score. However, some new DNA sequencing technologies do not directly measure the base sequence, but rather an encoded form, such as the two-base encoding considered here. In order to compare such data to a reference sequence, the data must be decoded into sequence. The decoding is deterministic, but the possibility of measurement errors requires searching among all possible error modes and resulting alignments to achieve an optimal balance of fewer errors versus greater sequence similarity. Results We present an extension of the standard dynamic programming method for local alignment, which simultaneously decodes the data and performs the alignment, maximizing a similarity score based on a weighted combination of errors and edits, and allowing an affine gap penalty. We also present simulations that demonstrate the performance characteristics of our two base encoded alignment method and contrast those with standard DNA sequence alignment under the same conditions. Conclusion The new local alignment algorithm for two-base encoded data has substantial power to properly detect and correct measurement errors while identifying underlying sequence variants, and facilitating genome re-sequencing efforts based on this form of sequence data. PMID:19508732

Variations in measured performance of CAD schemes due to database composition and scoring protocol

NASA Astrophysics Data System (ADS)

Nishikawa, Robert M.; Yarusso, Laura M.

1998-06-01

There is now a large effort towards developing computer- aided diagnosis (CAD) techniques. It is important to be able to compare performance of different approaches to be able to determine which ones are the most efficacious. There are currently a number of barriers preventing meaningful (statistical) comparisons, two of which are discussed in this paper: database composition and scoring protocol. We have examined how the choice of cases used to test a CAD scheme can affect its performance. We found that our computer scheme varied between a sensitivity of 100% to 77%, at a false-positive rate of 1.0 per image, with only 100% change in the composition of the database. To evaluate the performance of a CAD scheme the output of the computer must be graded. There are a number of different criteria that are being used by different investigators. We have found that for the same set of detection results, the measured sensitivity can be between 40 - 90% depending on the scoring methodology. Clearly consensus must be reached on these two issues in order for the field to make rapid progress. As it stands now, it is not possible to make meaningful comparisons of different techniques.

Noncontrast magnetic resonance angiography of the hand: improved arterial conspicuity by multidirectional flow-sensitive dephasing magnetization preparation in 3D balanced steady-state free precession imaging.

PubMed

Fan, Zhaoyang; Hodnett, Philip A; Davarpanah, Amir H; Scanlon, Timothy G; Sheehan, John J; Varga, John; Carr, James C; Li, Debiao

2011-08-01

: To develop a flow-sensitive dephasing (FSD) preparative scheme to facilitate multidirectional flow-signal suppression in 3-dimensional balanced steady-state free precession imaging and to validate the feasibility of the refined sequence for noncontrast magnetic resonance angiography (NC-MRA) of the hand. : A new FSD preparative scheme was developed that combines 2 conventional FSD modules. Studies using a flow phantom (gadolinium-doped water 15 cm/s) and the hands of 11 healthy volunteers (6 males and 5 females) were performed to compare the proposed FSD scheme with its conventional counterpart with respect to the signal suppression of multidirectional flow. In 9 of the 11 healthy subjects and 2 patients with suspected vasculitis and documented Raynaud phenomenon, respectively, 3-dimensional balanced steady-state free precession imaging coupled with the new FSD scheme was compared with spatial-resolution-matched (0.94 × 0.94 × 0.94 mm) contrast-enhanced magnetic resonance angiography (0.15 mmol/kg gadopentetate dimeglumine) in terms of overall image quality, venous contamination, motion degradation, and arterial conspicuity. : The proposed FSD scheme was able to suppress 2-dimensional flow signal in the flow phantom and hands and yielded significantly higher arterial conspicuity scores than the conventional scheme did on NC-MRA at the regions of common digitals and proper digitals. Compared with contrast-enhanced magnetic resonance angiography, the refined NC-MRA technique yielded comparable overall image quality and motion degradation, significantly less venous contamination, and significantly higher arterial conspicuity score at digital arteries. : The FSD-based NC-MRA technique is improved in the depiction of multidirectional flow by applying a 2-module FSD preparation, which enhances its potential to serve as an alternative magnetic resonance angiography technique for the assessment of hand vascular abnormalities.

Approximate treatment of semicore states in GW calculations with application to Au clusters.

PubMed

Xian, Jiawei; Baroni, Stefano; Umari, P

2014-03-28

We address the treatment of transition metal atoms in GW electronic-structure calculations within the plane-wave pseudo-potential formalism. The contributions of s and p semi-core electrons to the self-energy, which are essential to grant an acceptable accuracy, are dealt with using a recently proposed scheme whereby the exchange components are treated exactly at the G0W0 level, whereas a suitable approximation to the correlation components is devised. This scheme is benchmarked for small gold nano-clusters, resulting in ionization potentials, electron affinities, and density of states in very good agreement with those obtained from calculations where s and p semicore states are treated as valence orbitals, and allowing us to apply this same scheme to clusters of intermediate size, Au20 and Au32, that would be otherwise very difficult to deal with.

Approximate treatment of semicore states in GW calculations with application to Au clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xian, Jiawei; Baroni, Stefano; CNR-IOM Democritos, Theory-Elettra group, Trieste

We address the treatment of transition metal atoms in GW electronic-structure calculations within the plane-wave pseudo-potential formalism. The contributions of s and p semi-core electrons to the self-energy, which are essential to grant an acceptable accuracy, are dealt with using a recently proposed scheme whereby the exchange components are treated exactly at the G{sub 0}W{sub 0} level, whereas a suitable approximation to the correlation components is devised. This scheme is benchmarked for small gold nano-clusters, resulting in ionization potentials, electron affinities, and density of states in very good agreement with those obtained from calculations where s and p semicore statesmore » are treated as valence orbitals, and allowing us to apply this same scheme to clusters of intermediate size, Au{sub 20} and Au{sub 32}, that would be otherwise very difficult to deal with.« less

Effectiveness of vegetation-based biodiversity offset metrics as surrogates for ants.

PubMed

Hanford, Jayne K; Crowther, Mathew S; Hochuli, Dieter F

2017-02-01

Biodiversity offset schemes are globally popular policy tools for balancing the competing demands of conservation and development. Trading currencies for losses and gains in biodiversity value at development and credit sites are usually based on several vegetation attributes combined to yield a simple score (multimetric), but the score is rarely validated prior to implementation. Inaccurate biodiversity trading currencies are likely to accelerate global biodiversity loss through unrepresentative trades of losses and gains. We tested a model vegetation multimetric (i.e., vegetation structural and compositional attributes) typical of offset trading currencies to determine whether it represented measurable components of compositional and functional biodiversity. Study sites were located in remnant patches of a critically endangered ecological community in western Sydney, Australia, an area representative of global conflicts between conservation and expanding urban development. We sampled ant fauna composition with pitfall traps and enumerated removal by ants of native plant seeds from artificial seed containers (seed depots). Ants are an excellent model taxon because they are strongly associated with habitat complexity, respond rapidly to environmental change, and are functionally important at many trophic levels. The vegetation multimetric did not predict differences in ant community composition or seed removal, despite underlying assumptions that biodiversity trading currencies used in offset schemes represent all components of a site's biodiversity value. This suggests that vegetation multimetrics are inadequate surrogates for total biodiversity value. These findings highlight the urgent need to refine existing offsetting multimetrics to ensure they meet underlying assumptions of surrogacy. Despite the best intentions, offset schemes will never achieve their goal of no net loss of biodiversity values if trades are based on metrics unrepresentative of total biodiversity. © 2016 Society for Conservation Biology.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Factors affecting sustainability of rural water schemes in Swaziland

NASA Astrophysics Data System (ADS)

Peter, Graciana; Nkambule, Sizwe E.

The Millennium Development Goal (MDG) target to reduce the proportion of people without sustainable access to safe drinking water by the year 2015 has been met as of 2010, but huge disparities exist. Some regions, particularly Sub-Saharan Africa are lagging behind it is also in this region where up to 30% of the rural schemes are not functional at any given time. There is need for more studies on factors affecting sustainability and necessary measures which when implemented will improve the sustainability of rural water schemes. The main objective of this study was to assess the main factors affecting the sustainability of rural water schemes in Swaziland using a Multi-Criteria Analysis Approach. The main factors considered were: financial, social, technical, environmental and institutional. The study was done in Lubombo region. Fifteen functional water schemes in 11 communities were studied. Data was collected using questionnaires, checklist and focused group discussion guide. A total of 174 heads of households were interviewed. Statistical Package for Social Sciences (SPSS) was used to analyse the data and to calculate sustainability scores for water schemes. SPSS was also used to classify sustainability scores according to sustainability categories: sustainable, partially sustainable and non-sustainable. The averages of the ratings for the different sub-factors studied and the results on the sustainability scores for the sustainable, partially sustainable and non-sustainable schemes were then computed and compared to establish the main factors influencing sustainability of the water schemes. The results indicated technical and social factors as most critical while financial and institutional, although important, played a lesser role. Factors which contributed to the sustainability of water schemes were: functionality; design flow; water fetching time; ability to meet additional demand; use by population; equity; participation in decision making on operation and maintenance; existence of fund for operation and maintenance; willingness to contribute money; existence of a user’s committee; participation in the initial planning and design of the water scheme; and coordination between the local leaders and user’s committee. The main factors which made the schemes unsustainable were: long fetching time; non-involvement in decision making; lack of willingness to contribute funds; absence of users committee; and lack of cooperation between local leaders and the users committee. Water service providers should address the technical, social, financial and institutional factors identified affecting sustainability in their planning and implementation of rural water schemes.

Monte Carlo modeling and meteor showers

NASA Technical Reports Server (NTRS)

Kulikova, N. V.

1987-01-01

Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.

Market behavior and performance of different strategy evaluation schemes

NASA Astrophysics Data System (ADS)

Baek, Yongjoo; Lee, Sang Hoon; Jeong, Hawoong

2010-08-01

Strategy evaluation schemes are a crucial factor in any agent-based market model, as they determine the agents’ strategy preferences and consequently their behavioral pattern. This study investigates how the strategy evaluation schemes adopted by agents affect their performance in conjunction with the market circumstances. We observe the performance of three strategy evaluation schemes, the history-dependent wealth game, the trend-opposing minority game, and the trend-following majority game, in a stock market where the price is exogenously determined. The price is either directly adopted from the real stock market indices or generated with a Markov chain of order ≤2 . Each scheme’s success is quantified by average wealth accumulated by the traders equipped with the scheme. The wealth game, as it learns from the history, shows relatively good performance unless the market is highly unpredictable. The majority game is successful in a trendy market dominated by long periods of sustained price increase or decrease. On the other hand, the minority game is suitable for a market with persistent zigzag price patterns. We also discuss the consequence of implementing finite memory in the scoring processes of strategies. Our findings suggest under which market circumstances each evaluation scheme is appropriate for modeling the behavior of real market traders.

Integral reinforcement learning for continuous-time input-affine nonlinear systems with simultaneous invariant explorations.

PubMed

Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2015-05-01

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL (I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine system dynamics. First, we extend the concepts of exploration, integral temporal difference, and invariant admissibility to the target CT nonlinear system that is governed by a control policy plus a probing signal called an exploration. Then, we show input-to-state stability (ISS) and invariant admissibility of the closed-loop systems with the policies generated by integral policy iteration (I-PI) or invariantly admissible PI (IA-PI) method. Based on these, three online I-RL algorithms named explorized I-PI and integral Q -learning I, II are proposed, all of which generate the same convergent sequences as I-PI and IA-PI under the required excitation condition on the exploration. All the proposed methods are partially or completely model free, and can simultaneously explore the state space in a stable manner during the online learning processes. ISS, invariant admissibility, and convergence properties of the proposed methods are also investigated, and related with these, we show the design principles of the exploration for safe learning. Neural-network-based implementation methods for the proposed schemes are also presented in this paper. Finally, several numerical simulations are carried out to verify the effectiveness of the proposed methods.

Effect of Antipsychotic Type and Dose Changes on Tardive Dyskinesia and Parkinsonism Severity in Patients With a Serious Mental Illness: The Curaçao Extrapyramidal Syndromes Study XII.

PubMed

Mentzel, Charlotte L; Bakker, P Roberto; van Os, Jim; Drukker, Marjan; Matroos, Glenn E; Hoek, Hans W; Tijssen, Marina A J; van Harten, Peter N

2017-03-01

To test the efficacy of current treatment recommendations for parkinsonism and tardive dyskinesia (TD) severity in patients with severe mental illness (SMI). We present an 18-year prospective study including all 223 patients with SMI (as defined by the 1987 US National Institute of Mental Health, which were based on DSM-III-R diagnostic criteria) receiving care from the only psychiatric hospital of the former Netherlands Antilles. Eight clinical assessments (1992-2009) focused on movement disorders and medication use. Tardive dyskinesia was measured by the Abnormal Involuntary Movement Scale and parkinsonism by the Unified Parkinson's Disease Rating Scale. Antipsychotics were classified into first-generation antipsychotic (FGA) versus second-generation antipsychotic (SGA) and high versus low dopamine 2 (D₂) affinity categories. The effect that switching has within each category on subsequent movement scores was calculated separately by using time-lagged multilevel logistic regression models. There was a significant association between reduction in TD severity and starting/switching to an FGA (B = -3.54, P < .001) and starting/switching to a high D₂ affinity antipsychotic (B = -2.49, P < .01). Adding an SGA to existing FGA treatment was associated with reduction in TD severity (B = -2.43, P < .01). For parkinsonism, stopping antipsychotics predicted symptom reduction (B = -7.76, P < .01 in FGA/SGA-switch model; B = -7.74, P < .01 in D₂ affinity switch model), while starting a high D₂ affinity antipsychotic predicted an increase in symptoms (B = 3.29, P < .05 in D₂ affinity switch model). The results show that switching from an FGA to an SGA does not necessarily result in a reduction of TD or parkinsonism. Only stopping all antipsychotics reduces the severity of parkinsonism, and starting an FGA or a high D₂ affinity antipsychotic may reduce the severity of TD. © Copyright 2017 Physicians Postgraduate Press, Inc.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

White-nose syndrome pathology grading in Nearctic and Palearctic bats

PubMed Central

Pikula, Jiri; Amelon, Sybill K.; Bandouchova, Hana; Bartonička, Tomáš; Berkova, Hana; Brichta, Jiri; Hooper, Sarah; Kokurewicz, Tomasz; Kolarik, Miroslav; Köllner, Bernd; Kovacova, Veronika; Linhart, Petr; Piacek, Vladimir; Turner, Gregory G.; Zukal, Jan; Martínková, Natália

2017-01-01

While white-nose syndrome (WNS) has decimated hibernating bat populations in the Nearctic, species from the Palearctic appear to cope better with the fungal skin infection causing WNS. This has encouraged multiple hypotheses on the mechanisms leading to differential survival of species exposed to the same pathogen. To facilitate intercontinental comparisons, we proposed a novel pathogenesis-based grading scheme consistent with WNS diagnosis histopathology criteria. UV light-guided collection was used to obtain single biopsies from Nearctic and Palearctic bat wing membranes non-lethally. The proposed scheme scores eleven grades associated with WNS on histopathology. Given weights reflective of grade severity, the sum of findings from an individual results in weighted cumulative WNS pathology score. The probability of finding fungal skin colonisation and single, multiple or confluent cupping erosions increased with increase in Pseudogymnoascus destructans load. Increasing fungal load mimicked progression of skin infection from epidermal surface colonisation to deep dermal invasion. Similarly, the number of UV-fluorescent lesions increased with increasing weighted cumulative WNS pathology score, demonstrating congruence between WNS-associated tissue damage and extent of UV fluorescence. In a case report, we demonstrated that UV-fluorescence disappears within two weeks of euthermy. Change in fluorescence was coupled with a reduction in weighted cumulative WNS pathology score, whereby both methods lost diagnostic utility. While weighted cumulative WNS pathology scores were greater in the Nearctic than Palearctic, values for Nearctic bats were within the range of those for Palearctic species. Accumulation of wing damage probably influences mortality in affected bats, as demonstrated by a fatal case of Myotis daubentonii with natural WNS infection and healing in Myotis myotis. The proposed semi-quantitative pathology score provided good agreement between experienced raters, showing it to be a powerful and widely applicable tool for defining WNS severity. PMID:28767673

White-nose syndrome pathology grading in Nearctic and Palearctic bats.

PubMed

Pikula, Jiri; Amelon, Sybill K; Bandouchova, Hana; Bartonička, Tomáš; Berkova, Hana; Brichta, Jiri; Hooper, Sarah; Kokurewicz, Tomasz; Kolarik, Miroslav; Köllner, Bernd; Kovacova, Veronika; Linhart, Petr; Piacek, Vladimir; Turner, Gregory G; Zukal, Jan; Martínková, Natália

2017-01-01

While white-nose syndrome (WNS) has decimated hibernating bat populations in the Nearctic, species from the Palearctic appear to cope better with the fungal skin infection causing WNS. This has encouraged multiple hypotheses on the mechanisms leading to differential survival of species exposed to the same pathogen. To facilitate intercontinental comparisons, we proposed a novel pathogenesis-based grading scheme consistent with WNS diagnosis histopathology criteria. UV light-guided collection was used to obtain single biopsies from Nearctic and Palearctic bat wing membranes non-lethally. The proposed scheme scores eleven grades associated with WNS on histopathology. Given weights reflective of grade severity, the sum of findings from an individual results in weighted cumulative WNS pathology score. The probability of finding fungal skin colonisation and single, multiple or confluent cupping erosions increased with increase in Pseudogymnoascus destructans load. Increasing fungal load mimicked progression of skin infection from epidermal surface colonisation to deep dermal invasion. Similarly, the number of UV-fluorescent lesions increased with increasing weighted cumulative WNS pathology score, demonstrating congruence between WNS-associated tissue damage and extent of UV fluorescence. In a case report, we demonstrated that UV-fluorescence disappears within two weeks of euthermy. Change in fluorescence was coupled with a reduction in weighted cumulative WNS pathology score, whereby both methods lost diagnostic utility. While weighted cumulative WNS pathology scores were greater in the Nearctic than Palearctic, values for Nearctic bats were within the range of those for Palearctic species. Accumulation of wing damage probably influences mortality in affected bats, as demonstrated by a fatal case of Myotis daubentonii with natural WNS infection and healing in Myotis myotis. The proposed semi-quantitative pathology score provided good agreement between experienced raters, showing it to be a powerful and widely applicable tool for defining WNS severity.

A comparative study on resilience level between WHO health promoting schools and other schools among a Chinese population.

PubMed

Wong, Martin C S; Lee, Albert; Sun, Jing; Stewart, Donald; Cheng, Frances F K; Kan, Wing; Ho, Mandy

2009-06-01

The WHO health promoting school (HPS) approach covers key areas including school-based programmes improving students' psychological health, but there have been few studies evaluating the resilience performance of these schools. This study compared the resilience scores between schools within the healthy school award (HSA) scheme (HPS group) and those not (non-HPS group). We conducted a cross-sectional survey of grade-one students (aged 12), all teachers and parents of mainstream secondary schools recruited by stratified random sampling in one large Territory of Hong Kong using validated resilience questionnaires during November-December 2005. Four non-HPS and four HPS secondary schools were recruited, respectively, involving 1408 students, 891 parents and 91 teachers, with similar baseline characteristics. The HPS students were found to have better scores than non-HPS students (average age 12.4 year-old in both groups) in all dimensions with significantly higher scores in 'Peer Support' (p = 0.013), 'Making a Difference' (p = 0.011), 'About Me' (p = 0.027) and 'Generally Happy' (p = 0.011). There was no difference in the scores between non-HPS and HPS parents. The HPS teachers reported significantly higher scores in 'Health Policies' (p = 0.023), 'Social Environment' (p = 0.049), 'School Community Relations' (p = 0.048), 'Personal Skills Building' (p = 0.008) and 'Partnership & Health Services' (p = 0.047). The secondary HPS students and teachers reported significantly higher resilience scores than those of non-HPS. This study shows that the HSA scheme under WHO has the potential to exert positive changes in students and teachers and the concept of HPS is effective in building resilience among major school stakeholders.

Structure-Based Predictions of Activity Cliffs

PubMed Central

Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

2015-01-01

In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

Evaluating Prototype Tasks and Alternative Rating Schemes for a New ESL Writing Test through G-Theory

ERIC Educational Resources Information Center

Lee, Yong-Won; Kantor, Robert

2007-01-01

Possible integrated and independent tasks were pilot tested for the writing section of a new generation of the TOEFL[R] (Test of English as a Foreign Language[TM]). This study examines the impact of various rating designs and of the number of tasks and raters on the reliability of writing scores based on integrated and independent tasks from the…

Text analysis of MEDLINE for discovering functional relationships among genes: evaluation of keyword extraction weighting schemes.

PubMed

Liu, Ying; Navathe, Shamkant B; Pivoshenko, Alex; Dasigi, Venu G; Dingledine, Ray; Ciliax, Brian J

2006-01-01

One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

A frame selective dynamic programming approach for noise robust pitch estimation.

PubMed

Yarra, Chiranjeevi; Deshmukh, Om D; Ghosh, Prasanta Kumar

2018-04-01

The principles of the existing pitch estimation techniques are often different and complementary in nature. In this work, a frame selective dynamic programming (FSDP) method is proposed which exploits the complementary characteristics of two existing methods, namely, sub-harmonic to harmonic ratio (SHR) and sawtooth-wave inspired pitch estimator (SWIPE). Using variants of SHR and SWIPE, the proposed FSDP method classifies all the voiced frames into two classes-the first class consists of the frames where a confidence score maximization criterion is used for pitch estimation, while for the second class, a dynamic programming (DP) based approach is proposed. Experiments are performed on speech signals separately from KEELE, CSLU, and PaulBaghsaw corpora under clean and additive white Gaussian noise at 20, 10, 5, and 0 dB SNR conditions using four baseline schemes including SHR, SWIPE, and two DP based techniques. The pitch estimation performance of FSDP, when averaged over all SNRs, is found to be better than those of the baseline schemes suggesting the benefit of applying smoothness constraint using DP in selected frames in the proposed FSDP scheme. The VuV classification error from FSDP is also found to be lower than that from all four baseline schemes in almost all SNR conditions on three corpora.

Brute-Force Approach for Mass Spectrometry-Based Variant Peptide Identification in Proteogenomics without Personalized Genomic Data

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Lobas, Anna A.; Levitsky, Lev I.; Moshkovskii, Sergei A.; Gorshkov, Mikhail V.

2018-02-01

In a proteogenomic approach based on tandem mass spectrometry analysis of proteolytic peptide mixtures, customized exome or RNA-seq databases are employed for identifying protein sequence variants. However, the problem of variant peptide identification without personalized genomic data is important for a variety of applications. Following the recent proposal by Chick et al. (Nat. Biotechnol. 33, 743-749, 2015) on the feasibility of such variant peptide search, we evaluated two available approaches based on the previously suggested "open" search and the "brute-force" strategy. To improve the efficiency of these approaches, we propose an algorithm for exclusion of false variant identifications from the search results involving analysis of modifications mimicking single amino acid substitutions. Also, we propose a de novo based scoring scheme for assessment of identified point mutations. In the scheme, the search engine analyzes y-type fragment ions in MS/MS spectra to confirm the location of the mutation in the variant peptide sequence.

Networked iterative learning control design for discrete-time systems with stochastic communication delay in input and output channels

NASA Astrophysics Data System (ADS)

Liu, Jian; Ruan, Xiaoe

2017-07-01

This paper develops two kinds of derivative-type networked iterative learning control (NILC) schemes for repetitive discrete-time systems with stochastic communication delay occurred in input and output channels and modelled as 0-1 Bernoulli-type stochastic variable. In the two schemes, the delayed signal of the current control input is replaced by the synchronous input utilised at the previous iteration, whilst for the delayed signal of the system output the one scheme substitutes it by the synchronous predetermined desired trajectory and the other takes it by the synchronous output at the previous operation, respectively. In virtue of the mathematical expectation, the tracking performance is analysed which exhibits that for both the linear time-invariant and nonlinear affine systems the two kinds of NILCs are convergent under the assumptions that the probabilities of communication delays are adequately constrained and the product of the input-output coupling matrices is full-column rank. Last, two illustrative examples are presented to demonstrate the effectiveness and validity of the proposed NILC schemes.

Comparison of different incremental analysis update schemes in a realistic assimilation system with Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Yan, Y.; Barth, A.; Beckers, J. M.; Brankart, J. M.; Brasseur, P.; Candille, G.

2017-07-01

In this paper, three incremental analysis update schemes (IAU 0, IAU 50 and IAU 100) are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The difference between the three IAU schemes lies on the position of the increment update window. The relevance of each IAU scheme is evaluated through analyses on both thermohaline and dynamical variables. The validation of the assimilation results is performed according to both deterministic and probabilistic metrics against different sources of observations. For deterministic validation, the ensemble mean and the ensemble spread are compared to the observations. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centred random variable (RCRV) score. The obtained results show that 1) the IAU 50 scheme has the same performance as the IAU 100 scheme 2) the IAU 50/100 schemes outperform the IAU 0 scheme in error covariance propagation for thermohaline variables in relatively stable region, while the IAU 0 scheme outperforms the IAU 50/100 schemes in dynamical variables estimation in dynamically active region 3) in case with sufficient number of observations and good error specification, the impact of IAU schemes is negligible. The differences between the IAU 0 scheme and the IAU 50/100 schemes are mainly due to different model integration time and different instability (density inversion, large vertical velocity, etc.) induced by the increment update. The longer model integration time with the IAU 50/100 schemes, especially the free model integration, on one hand, allows for better re-establishment of the equilibrium model state, on the other hand, smooths the strong gradients in dynamically active region.

Studies of flerovium and element 115 homologs with macrocyclic extractants

NASA Astrophysics Data System (ADS)

Despotopulos, John Dustin

Study of the chemistry of the heaviest elements, Z ? 104, poses a unique challenge due to their low production cross-sections and short half-lives. Chemistry also must be studied on the one-atom-at-a-time scale, requiring automated, fast, and very efficient chemical schemes. Recent studies of the chemical behavior of copernicium (Cn, element 112) and flerovium (Fl, element 114) together with the discovery of isotopes of these elements with half-lives suitable for chemical studies have spurred a renewed interest in the development of rapid systems designed to study the chemical properties of elements with Z ≥ 114. This dissertation explores both extraction chromatography and solvent extraction as methods for development of a rapid chemical separation scheme for the homologs of flerovium (Pb, Sn, Hg) and element 115 (Bi, Sb), with the goal of developing a chemical scheme that, in the future, can be applied to on-line chemistry of both Fl and element 115. Macrocyclic extractants, specifically crown ethers and their derivatives, were chosen for these studies. Carrier-free radionuclides, used in these studies, of the homologs of Fl and element 115 were obtained by proton activation of high purity metal foils at the Lawrence Livermore National Laboratory (LLNL) Center for Accelerator Mass Spectrometry (CAMS): natIn(p,n)113Sn, natSn(p,n)124Sb, and Au(p,n)197m,gHg. The carrier-free activity was separated from the foils by novel separation schemes based on ion exchange and extraction chromatography techniques. Carrier-free Pb and Bi isotopes were obtained from development of a novel generator based on cation exchange chromatography using the 232U parent to generate 212Pb and 212Bi. Crown ethers show high selectivity for metal ions based on their size compared to the negatively charged cavity of the ether. Extraction by crown ethers occur based on electrostatic ion-dipole interactions between the negatively charged ring atoms (oxygen, sulfur, etc.) and the positively charged metal cations. Extraction chromatography resins produced by Eichrom Technologies, specifically the Pb resin based on di-t-byutlcyclohexano-18-crown-6, were chosen as a starting point for these studies. Simple chemical systems based solely on HCl matrices were explored to determine the extent of extraction for Pb, Sn and Hg on the resin. The kinetics and mechanism of extraction were also explored to determine suitability for a Fl chemical experiment. Systems based on KI/HCl and KI/HNO3 were explored for Bi and Sb. In both cases suitable separations, with high separation factors, were performed with vacuum flow columns containing the Pb-resin. Unfortunately the kinetics of uptake for Hg are far too slow on the traditional crown-ether to perform a Fl experiment and obtain whether or not Fl has true Hg-like character or not. However, the kinetics of Pb and Sn are more than sufficient for a Fl experiment to differentiate between Pb- or Sn-like character. To assess this kinetic issue a novel macrocyclic extractant based on sulfur donors was synthesized. Hexathia-18-crown-6, the sulfur analog of 18-crown-6, was synthesized based with by a template reaction using high dilution techniques. The replacement of oxygen ring atoms with sulfur should give the extractant a softer character, which should allow for far greater affinity toward soft metals such as Hg and Pb. From HCl matrices hexathia-18-crown-6 showed far greater kinetics and affinity for Hg than the Pb-resin; however, no affinity for Pb or Sn was seen. This presumably is due to the fact the charge density of sulfur crown ethers does not point to the center of the ring, and future synthesis of a substituted sulfur crown ether which forces the charge density to mimic that of the traditional crown ether should enable extraction of Pb and Sn to a greater extent than with the Pb-resin. Initial studies show promise for the separation of Bi and Sb from HCl matrices using hexathia-18-crown-6. Other macrocyclic extractants, including 2,2,2-cryptand, calix[6]arene and tetrathia-12-crown-4, were also investigated for comparison to the crown ethers. It was noted that these extractants are inferior compared to the crown and thiacrown ethers for extraction of Fl and element 115 homologs. A potential chemical system for Fl was established based on the Eichrom Pb resin, and insight to an improved system based on thiacrown ethers is presented.

Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study

NASA Astrophysics Data System (ADS)

Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Montes, Matthieu

2018-01-01

The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.

Evaluation of Video Image Analysis (VIA) technology to predict meat yield of sheep carcasses on-line under UK abattoir conditions.

PubMed

Rius-Vilarrasa, E; Bünger, L; Maltin, C; Matthews, K R; Roehe, R

2009-05-01

The Meat and Livestock Commission's (MLC) EUROP classification based scheme and Video Image Analysis (VIA) system were compared in their ability to predict weights of primal carcass joints. A total of 443 commercial lamb carcasses under 12 months of age and mixed gender were selected by their cold carcass weight (CCW), conformation and fat scores. Lamb carcasses were classified for conformation and fatness, scanned by the VIA system and dissected into primal joints of leg, chump, loin, breast and shoulder. After adjustment for CCW, the estimation of primal joints using MLC EUROP scores showed high coefficients of determination (R(2)) in the range of 0.82-0.99. The use of VIA always resulted in equal or higher R(2). The precision measured as root mean square error (RMSE) was 27% (leg), 13% (chump), 1% (loin), 11% (breast), 5% (shoulders) and 13% (total primals) higher using VIA than MLC carcass information. Adjustment for slaughter day and gender effects indicated that estimations of primal joints using MLC EUROP scores were more sensitive to these factors than using VIA. This was consistent with an increase in stability of the prediction model of 28%, 11%, 2%, 12%, 6% and 14% for leg, chump, loin, breast and shoulder and total primals, respectively, using VIA compared to MLC EUROP scores. Consequently, VIA was capable of improving the prediction of primal meat yields compared to the current MLC EUROP carcass classification scheme used in the UK abattoirs.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

PubMed

Nilsson, Ingemar; Polla, Magnus O

2012-10-01

Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

Enrichment and Analysis of Non-enzymatically Glycated Peptides: Boronate Affinity Chromatography Coupled with Electron Transfer Dissociation Mass Spectrometry

PubMed Central

Zhang, Qibin; Tang, Ning; Brock, Jonathan W. C.; Mottaz, Heather M.; Ames, Jennifer M.; Baynes, John W.; Smith, Richard D.; Metz, Thomas O.

2008-01-01

Non-enzymatic glycation of peptides and proteins by D-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. ETD fragmentation mode permitted identification of a significantly higher number of glycated peptides (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing enrichment on first the protein and then the peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS and using ETD as the fragmentation mode is an efficient approach for analysis of glycated proteins and may have broad application in studies of diabetes mellitus. PMID:17488106

Tag-Based Social Image Search: Toward Relevant and Diverse Results

NASA Astrophysics Data System (ADS)

Yang, Kuiyuan; Wang, Meng; Hua, Xian-Sheng; Zhang, Hong-Jiang

Recent years have witnessed a great success of social media websites. Tag-based image search is an important approach to access the image content of interest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the content of images and their associated tags. First, it estimates the relevance scores of images with respect to the query term based on both visual information of images and semantic information of associated tags. Then semantic similarities of social images are estimated based on their tags. Based on the relevance scores and the similarities, the ranking list is generated by a greedy ordering algorithm which optimizes Average Diverse Precision (ADP), a novel measure that is extended from the conventional Average Precision (AP). Comprehensive experiments and user studies demonstrate the effectiveness of the approach.

Rapid, topology-based particle tracking for high-resolution measurements of large complex 3D motion fields.

PubMed

Patel, Mohak; Leggett, Susan E; Landauer, Alexander K; Wong, Ian Y; Franck, Christian

2018-04-03

Spatiotemporal tracking of tracer particles or objects of interest can reveal localized behaviors in biological and physical systems. However, existing tracking algorithms are most effective for relatively low numbers of particles that undergo displacements smaller than their typical interparticle separation distance. Here, we demonstrate a single particle tracking algorithm to reconstruct large complex motion fields with large particle numbers, orders of magnitude larger than previously tractably resolvable, thus opening the door for attaining very high Nyquist spatial frequency motion recovery in the images. Our key innovations are feature vectors that encode nearest neighbor positions, a rigorous outlier removal scheme, and an iterative deformation warping scheme. We test this technique for its accuracy and computational efficacy using synthetically and experimentally generated 3D particle images, including non-affine deformation fields in soft materials, complex fluid flows, and cell-generated deformations. We augment this algorithm with additional particle information (e.g., color, size, or shape) to further enhance tracking accuracy for high gradient and large displacement fields. These applications demonstrate that this versatile technique can rapidly track unprecedented numbers of particles to resolve large and complex motion fields in 2D and 3D images, particularly when spatial correlations exist.

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

Perfect Detection of Spikes in the Linear Sub-threshold Dynamics of Point Neurons

PubMed Central

Krishnan, Jeyashree; Porta Mana, PierGianLuca; Helias, Moritz; Diesmann, Markus; Di Napoli, Edoardo

2018-01-01

Spiking neuronal networks are usually simulated with one of three main schemes: the classical time-driven and event-driven schemes, and the more recent hybrid scheme. All three schemes evolve the state of a neuron through a series of checkpoints: equally spaced in the first scheme and determined neuron-wise by spike events in the latter two. The time-driven and the hybrid scheme determine whether the membrane potential of a neuron crosses a threshold at the end of the time interval between consecutive checkpoints. Threshold crossing can, however, occur within the interval even if this test is negative. Spikes can therefore be missed. The present work offers an alternative geometric point of view on neuronal dynamics, and derives, implements, and benchmarks a method for perfect retrospective spike detection. This method can be applied to neuron models with affine or linear subthreshold dynamics. The idea behind the method is to propagate the threshold with a time-inverted dynamics, testing whether the threshold crosses the neuron state to be evolved, rather than vice versa. Algebraically this translates into a set of inequalities necessary and sufficient for threshold crossing. This test is slower than the imperfect one, but can be optimized in several ways. Comparison confirms earlier results that the imperfect tests rarely miss spikes (less than a fraction 1/108 of missed spikes) in biologically relevant settings. PMID:29379430

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

PubMed

Salaniwal, Sumeet; Manas, Eric S; Alvarez, Juan C; Unwalla, Rayomand J

2007-02-01

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method. Copyright 2006 Wiley-Liss, Inc.

Developing a contributing factor classification scheme for Rasmussen's AcciMap: Reliability and validity evaluation.

PubMed

Goode, N; Salmon, P M; Taylor, N Z; Lenné, M G; Finch, C F

2017-10-01

One factor potentially limiting the uptake of Rasmussen's (1997) Accimap method by practitioners is the lack of a contributing factor classification scheme to guide accident analyses. This article evaluates the intra- and inter-rater reliability and criterion-referenced validity of a classification scheme developed to support the use of Accimap by led outdoor activity (LOA) practitioners. The classification scheme has two levels: the system level describes the actors, artefacts and activity context in terms of 14 codes; the descriptor level breaks the system level codes down into 107 specific contributing factors. The study involved 11 LOA practitioners using the scheme on two separate occasions to code a pre-determined list of contributing factors identified from four incident reports. Criterion-referenced validity was assessed by comparing the codes selected by LOA practitioners to those selected by the method creators. Mean intra-rater reliability scores at the system (M = 83.6%) and descriptor (M = 74%) levels were acceptable. Mean inter-rater reliability scores were not consistently acceptable for both coding attempts at the system level (M T1  = 68.8%; M T2  = 73.9%), and were poor at the descriptor level (M T1  = 58.5%; M T2  = 64.1%). Mean criterion referenced validity scores at the system level were acceptable (M T1  = 73.9%; M T2  = 75.3%). However, they were not consistently acceptable at the descriptor level (M T1  = 67.6%; M T2  = 70.8%). Overall, the results indicate that the classification scheme does not currently satisfy reliability and validity requirements, and that further work is required. The implications for the design and development of contributing factors classification schemes are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two Simple and Efficient Algorithms to Compute the SP-Score Objective Function of a Multiple Sequence Alignment.

PubMed

Ranwez, Vincent

2016-01-01

Multiple sequence alignment (MSA) is a crucial step in many molecular analyses and many MSA tools have been developed. Most of them use a greedy approach to construct a first alignment that is then refined by optimizing the sum of pair score (SP-score). The SP-score estimation is thus a bottleneck for most MSA tools since it is repeatedly required and is time consuming. Given an alignment of n sequences and L sites, I introduce here optimized solutions reaching O(nL) time complexity for affine gap cost, instead of O(n2L), which are easy to implement.

Limited utility of residue masking for positive-selection inference.

PubMed

Spielman, Stephanie J; Dawson, Eric T; Wilke, Claus O

2014-09-01

Errors in multiple sequence alignments (MSAs) can reduce accuracy in positive-selection inference. Therefore, it has been suggested to filter MSAs before conducting further analyses. One widely used filter, Guidance, allows users to remove MSA positions aligned with low confidence. However, Guidance's utility in positive-selection inference has been disputed in the literature. We have conducted an extensive simulation-based study to characterize fully how Guidance impacts positive-selection inference, specifically for protein-coding sequences of realistic divergence levels. We also investigated whether novel scoring algorithms, which phylogenetically corrected confidence scores, and a new gap-penalization score-normalization scheme improved Guidance's performance. We found that no filter, including original Guidance, consistently benefitted positive-selection inferences. Moreover, all improvements detected were exceedingly minimal, and in certain circumstances, Guidance-based filters worsened inferences. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

PF2fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps.

PubMed

Bettadapura, Radhakrishna; Rasheed, Muhibur; Vollrath, Antje; Bajaj, Chandrajit

2015-10-01

There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF(2) fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF(2) fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF(2) fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF(2) fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF(2) fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF(2) fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search.

PF2 fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps

PubMed Central

Bettadapura, Radhakrishna; Rasheed, Muhibur; Vollrath, Antje; Bajaj, Chandrajit

2015-01-01

There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF2 fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF2 fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF2 fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF2 fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF2 fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF2 fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search. PMID:26469938

The Effect of Performance-Based Financial Incentives on Improving Health Care Provision in Burundi: A Controlled Cohort Study

PubMed Central

Rudasingwa, Martin; Soeters, Robert; Bossuyt, Michel

2015-01-01

To strengthen the health care delivery, the Burundian Government in collaboration with international NGOs piloted performance-based financing (PBF) in 2006. The health facilities were assigned - by using a simple matching method - to begin PBF scheme or to continue with the traditional input-based funding. Our objective was to analyse the effect of that PBF scheme on the quality of health services between 2006 and 2008. We conducted the analysis in 16 health facilities with PBF scheme and 13 health facilities without PBF scheme. We analysed the PBF effect by using 58 composite quality indicators of eight health services: Care management, outpatient care, maternity care, prenatal care, family planning, laboratory services, medicines management and materials management. The differences in quality improvement in the two groups of health facilities were performed applying descriptive statistics, a paired non-parametric Wilcoxon Signed Ranks test and a simple difference-in-difference approach at a significance level of 5%. We found an improvement of the quality of care in the PBF group and a significant deterioration in the non-PBF group in the same four health services: care management, outpatient care, maternity care, and prenatal care. The findings suggest a PBF effect of between 38 and 66 percentage points (p<0.001) in the quality scores of care management, outpatient care, prenatal care, and maternal care. We found no PBF effect on clinical support services: laboratory services, medicines management, and material management. The PBF scheme in Burundi contributed to the improvement of the health services that were strongly under the control of medical personnel (physicians and nurses) in a short time of two years. The clinical support services that did not significantly improved were strongly under the control of laboratory technicians, pharmacists and non-medical personnel. PMID:25948432

Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting

PubMed Central

Viriri, Serestina; Tapamo, Jules R.

2012-01-01

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. PMID:22666032

Registration of heat capacity mapping mission day and night images

NASA Technical Reports Server (NTRS)

Watson, K.; Hummer-Miller, S.; Sawatzky, D. L.

1982-01-01

Registration of thermal images is complicated by distinctive differences in the appearance of day and night features needed as control in the registration process. These changes are unlike those that occur between Landsat scenes and pose unique constraints. Experimentation with several potentially promising techniques has led to selection of a fairly simple scheme for registration of data from the experimental thermal satellite HCMM using an affine transformation. Two registration examples are provided.

Molecular Innovations Toward Theranostics of Aggressive Prostate Cancer

DTIC Science & Technology

2014-09-01

specific membrane antigen ( PSMA ) for prostate cancer theranostic application. Task 5 (Months 9 – 30): In vivo and PET/CT imaging evaluation of the...separate the entire synthesis into several subunits as shown in Scheme 1. The PSMA targeting ligand 4 has been synthesized in a conventional chemistry way...6]. To retain the PSMA targeting ligand affinity after integration into the MDCs, a PEG5 and a Boc-lysine linker has been introduced to form

From pull-down data to protein interaction networks and complexes with biological relevance.

PubMed

Zhang, Bing; Park, Byung-Hoon; Karpinets, Tatiana; Samatova, Nagiza F

2008-04-01

Recent improvements in high-throughput Mass Spectrometry (MS) technology have expedited genome-wide discovery of protein-protein interactions by providing a capability of detecting protein complexes in a physiological setting. Computational inference of protein interaction networks and protein complexes from MS data are challenging. Advances are required in developing robust and seamlessly integrated procedures for assessment of protein-protein interaction affinities, mathematical representation of protein interaction networks, discovery of protein complexes and evaluation of their biological relevance. A multi-step but easy-to-follow framework for identifying protein complexes from MS pull-down data is introduced. It assesses interaction affinity between two proteins based on similarity of their co-purification patterns derived from MS data. It constructs a protein interaction network by adopting a knowledge-guided threshold selection method. Based on the network, it identifies protein complexes and infers their core components using a graph-theoretical approach. It deploys a statistical evaluation procedure to assess biological relevance of each found complex. On Saccharomyces cerevisiae pull-down data, the framework outperformed other more complicated schemes by at least 10% in F(1)-measure and identified 610 protein complexes with high-functional homogeneity based on the enrichment in Gene Ontology (GO) annotation. Manual examination of the complexes brought forward the hypotheses on cause of false identifications. Namely, co-purification of different protein complexes as mediated by a common non-protein molecule, such as DNA, might be a source of false positives. Protein identification bias in pull-down technology, such as the hydrophilic bias could result in false negatives.

A novel single thruster control strategy for spacecraft attitude stabilization

NASA Astrophysics Data System (ADS)

Godard; Kumar, Krishna Dev; Zou, An-Min

2013-05-01

Feasibility of achieving three axis attitude stabilization using a single thruster is explored in this paper. Torques are generated using a thruster orientation mechanism with which the thrust vector can be tilted on a two axis gimbal. A robust nonlinear control scheme is developed based on the nonlinear kinematic and dynamic equations of motion of a rigid body spacecraft in the presence of gravity gradient torque and external disturbances. The spacecraft, controlled using the proposed concept, constitutes an underactuated system (a system with fewer independent control inputs than degrees of freedom) with nonlinear dynamics. Moreover, using thruster gimbal angles as control inputs make the system non-affine (control terms appear nonlinearly in the state equation). This necessitates the control algorithms to be developed based on nonlinear control theory since linear control methods are not directly applicable. The stability conditions for the spacecraft attitude motion for robustness against uncertainties and disturbances are derived to establish the regions of asymptotic 3-axis attitude stabilization. Several numerical simulations are presented to demonstrate the efficacy of the proposed controller and validate the theoretical results. The control algorithm is shown to compensate for time-varying external disturbances including solar radiation pressure, aerodynamic forces, and magnetic disturbances; and uncertainties in the spacecraft inertia parameters. The numerical results also establish the robustness of the proposed control scheme to negate disturbances caused by orbit eccentricity.

Binding free energy prediction in strongly hydrophobic biomolecular systems.

PubMed

Charlier, Landry; Nespoulous, Claude; Fiorucci, Sébastien; Antonczak, Serge; Golebiowski, Jérome

2007-11-21

We present a comparison of various computational approaches aiming at predicting the binding free energy in ligand-protein systems where the ligand is located within a highly hydrophobic cavity. The relative binding free energy between similar ligands is obtained by means of the thermodynamic integration (TI) method and compared to experimental data obtained through isothermal titration calorimetry measurements. The absolute free energy of binding prediction was obtained on a similar system (a pyrazine derivative bound to a lipocalin) by TI, potential of mean force (PMF) and also by means of the MMPBSA protocols. Although the TI protocol performs poorly either with an explicit or an implicit solvation scheme, the PMF calculation using an implicit solvation scheme leads to encouraging results, with a prediction of the binding affinity being 2 kcal mol(-1) lower than the experimental value. The use of an implicit solvation scheme appears to be well suited for the study of such hydrophobic systems, due to the lack of water molecules within the binding site.

Reduction of false-positives in a CAD scheme for automated detection of architectural distortion in digital mammography

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Mencattini, Arianna; Casti, Paola; Martinelli, Eugenio; di Natale, Corrado; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2018-02-01

This paper proposes a method to reduce the number of false-positives (FP) in a computer-aided detection (CAD) scheme for automated detection of architectural distortion (AD) in digital mammography. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automated detection of AD in breast images. The usual approach is automatically detect possible sites of AD in a mammographic image (segmentation step) and then use a classifier to eliminate the false-positives and identify the suspicious regions (classification step). This paper focus on the optimization of the segmentation step to reduce the number of FPs that is used as input to the classifier. The proposal is to use statistical measurements to score the segmented regions and then apply a threshold to select a small quantity of regions that should be submitted to the classification step, improving the detection performance of a CAD scheme. We evaluated 12 image features to score and select suspicious regions of 74 clinical Full-Field Digital Mammography (FFDM). All images in this dataset contained at least one region with AD previously marked by an expert radiologist. The results showed that the proposed method can reduce the false positives of the segmentation step of the CAD scheme from 43.4 false positives (FP) per image to 34.5 FP per image, without increasing the number of false negatives.

Customer satisfaction survey to improve the European cystic fibrosis external quality assessment scheme.

PubMed

Berwouts, Sarah; Dequeker, Elisabeth

2011-08-01

The Cystic Fibrosis European Network, coordinated from within the Katholieke Universiteit Leuven, is the provider of the European cystic fibrosis external quality assessment (EQA) scheme. The network aimed to seek feedback from laboratories that participated in the cystic fibrosis scheme in order to improve services offered. In this study we analysed responses to an on-line customer satisfaction survey conducted between September and November 2009. The survey was sent to 213 laboratories that participated in the cystic fibrosis EQA scheme of 2008; 69 laboratories (32%) responded. Scores for importance and satisfaction were obtained from a five-point Likert scale for 24 attributes. A score of one corresponded to very dissatisfied/very unimportant and five corresponded to very satisfied/very important. Means were calculated and placed in a two-dimensional grid (importance-satisfaction analysis). Means were subtracted from each other to obtain gap values (gap-analysis). No attribute had a mean score below 3.63. The overall mean of satisfaction was 4.35. Opportunities for improvement enclosed clarity, usefulness and completeness of the general report and individual comments, and user-friendliness of the electronic datasheet. This type of customer satisfaction survey was a valuable instrument to identify opportunities to improve the cystic fibrosis EQA scheme. It should be conducted on a regular basis to reveal new opportunities in the future and to assess effectiveness of actions taken. Moreover, it could be a model for other EQA providers seeking feedback from participants. Overall, the customer satisfaction survey provided a powerful quality of care improvement tool.

Fibulin-1 purification from human plasma using affinity chromatography on Factor H-Sepharose

PubMed Central

DiScipio, Richard G.; Liddington, Robert C.; Schraufstatter, Ingrid U.

2016-01-01

A method is reported to purify Fibulin-1 from human plasma resulting in a 36% recovery. The steps involve removal of the cryoglobulin and the vitamin K dependent proteins followed by polyethylene glycol and ammonium sulfate precipitations, DEAE-Sephadex column chromatography and finally Factor H-Sepharose affinity purification. The procedure is designed to be integrated into an overall scheme for the isolation of over 30 plasma proteins from a single batch of human plasma. Results from mass spectroscopy, SDS-PAGE, and Western blotting indicate that human plasma Fibulin-1 is a single chain of the largest isotype. Functional binding assays demonstrated calcium ion dependent interaction of Fibulin-1 for fibrinogen, fibronectin, and Factor H. The procedure described is the first to our knowledge that enables a large scale purification of Fibulin-1 from human plasma. PMID:26826315

A Scheme for Regrouping WISC-R Subtests.

ERIC Educational Resources Information Center

Groff, Martin G.; Hubble, Larry M.

1984-01-01

Reviews WISC-R factor analytic findings for developing a scheme for regrouping WISC-R subtests, consisting of verbal comprehension and spatial subtests. Subtests comprising these groupings are shown to have more common variance than specific variance and cluster together consistently across the samples of WISC-R scores. (Author/JAC)

Context-Sensitive Markov Models for Peptide Scoring and Identification from Tandem Mass Spectrometry

PubMed Central

Grover, Himanshu; Wallstrom, Garrick; Wu, Christine C.

2013-01-01

Abstract Peptide and protein identification via tandem mass spectrometry (MS/MS) lies at the heart of proteomic characterization of biological samples. Several algorithms are able to search, score, and assign peptides to large MS/MS datasets. Most popular methods, however, underutilize the intensity information available in the tandem mass spectrum due to the complex nature of the peptide fragmentation process, thus contributing to loss of potential identifications. We present a novel probabilistic scoring algorithm called Context-Sensitive Peptide Identification (CSPI) based on highly flexible Input-Output Hidden Markov Models (IO-HMM) that capture the influence of peptide physicochemical properties on their observed MS/MS spectra. We use several local and global properties of peptides and their fragment ions from literature. Comparison with two popular algorithms, Crux (re-implementation of SEQUEST) and X!Tandem, on multiple datasets of varying complexity, shows that peptide identification scores from our models are able to achieve greater discrimination between true and false peptides, identifying up to ∼25% more peptides at a False Discovery Rate (FDR) of 1%. We evaluated two alternative normalization schemes for fragment ion-intensities, a global rank-based and a local window-based. Our results indicate the importance of appropriate normalization methods for learning superior models. Further, combining our scores with Crux using a state-of-the-art procedure, Percolator, we demonstrate the utility of using scoring features from intensity-based models, identifying ∼4-8 % additional identifications over Percolator at 1% FDR. IO-HMMs offer a scalable and flexible framework with several modeling choices to learn complex patterns embedded in MS/MS data. PMID:23289783

Exploring the binding pathways of the 14-3-3ζ protein: Structural and free-energy profiles revealed by Hamiltonian replica exchange molecular dynamics with distancefield distance restraints

PubMed Central

Nagy, Gabor; Oostenbrink, Chris; Hritz, Jozef

2017-01-01

The 14-3-3 protein family performs regulatory functions in eukaryotic organisms by binding to a large number of phosphorylated protein partners. Whilst the binding mode of the phosphopeptides within the primary 14-3-3 binding site is well established based on the crystal structures of their complexes, little is known about the binding process itself. We present a computational study of the process by which phosphopeptides bind to the 14-3-3ζ protein. Applying a novel scheme combining Hamiltonian replica exchange molecular dynamics and distancefield restraints allowed us to map and compare the most likely phosphopeptide-binding pathways to the 14-3-3ζ protein. The most important structural changes to the protein and peptides involved in the binding process were identified. In order to bind phosphopeptides to the primary interaction site, the 14-3-3ζ adopted a newly found wide-opened conformation. Based on our findings we additionally propose a secondary interaction site on the inner surface of the 14-3-3ζ dimer, and a direct interference on the binding process by the flexible C-terminal tail. A minimalistic model was designed to allow for the efficient calculation of absolute binding affinities. Binding affinities calculated from the potential of mean force along the binding pathway are in line with the available experimental estimates for two of the studied systems. PMID:28727767

The reliability of axis V of the multiaxial classification scheme.

PubMed

van Goor-Lambo, G

1987-07-01

In a reliability study concerning axis V (abnormal psychosocial situations) of the Multiaxial classification scheme for psychiatric disorders in childhood and adolescence, it was found that the level of agreement in scoring was adequate for only 2 out of 12 categories. A proposal for a modification of axis V was made, including a differentiation and regrouping of the categories and an adjustment of the descriptions in the glossary. With this modification of axis V another reliability study was carried out, in which the level of agreement in scoring was adequate for 12 out of 16 categories.

Efficacy and Safety of MIN-101: A 12-Week Randomized, Double-Blind, Placebo-Controlled Trial of a New Drug in Development for the Treatment of Negative Symptoms in Schizophrenia.

PubMed

Davidson, Michael; Saoud, Jay; Staner, Corinne; Noel, Nadine; Luthringer, Elisabeth; Werner, Sandra; Reilly, Joseph; Schaffhauser, Jean-Yves; Rabinowitz, Jonathan; Weiser, Mark; Luthringer, Remy

2017-12-01

The authors assessed the efficacy, safety, and tolerability of MIN-101, a compound with affinities for sigma-2 and 5-HT 2A receptors and no direct dopamine affinities, in comparison with placebo in treating negative symptoms in stabilized patients with schizophrenia. The trial enrolled 244 patients who had been symptomatically stable for at least 3 months and had scores of at least 20 on the negative subscale of the Positive and Negative Syndrome Scale (PANSS). After at least 5 days' withdrawal from all antipsychotic medication, patients were randomly assigned to receive placebo or 32 mg/day or 64 mg/day of MIN-101 for 12 weeks. The primary outcome measure was the PANSS negative factor score (pentagonal structure model). Secondary outcome measures were PANSS total score and scores on the Clinical Global Impressions Scale (CGI), the Brief Negative Symptom Scale, the Brief Assessment of Cognition in Schizophrenia, and the Calgary Depression Scale for Schizophrenia. A statistically significant difference in PANSS negative factor score was observed, with lower scores for the MIN-101 32 mg/day and 64 mg/day groups compared with the placebo group (effect sizes, d=0.45 and d=0.57, respectively). Supporting these findings were similar effects on several of the secondary outcome measures, such as the PANSS negative symptom, total, and activation factor scores, the CGI severity item, and the Brief Negative Symptom Scale. There were no statistically significant differences in PANSS positive scale score between the MIN-101 and placebo groups. No clinically significant changes were observed in vital signs, routine laboratory values, weight, metabolic indices, and Abnormal Involuntary Movement Scale score. MIN-101 demonstrated statistically significant efficacy in reducing negative symptoms and good tolerability in stable schizophrenia patients.

Improved pose and affinity predictions using different protocols tailored on the basis of data availability

NASA Astrophysics Data System (ADS)

Prathipati, Philip; Nagao, Chioko; Ahmad, Shandar; Mizuguchi, Kenji

2016-09-01

The D3R 2015 grand drug design challenge provided a set of blinded challenges for evaluating the applicability of our protocols for pose and affinity prediction. In the present study, we report the application of two different strategies for the two D3R protein targets HSP90 and MAP4K4. HSP90 is a well-studied target system with numerous co-crystal structures and SAR data. Furthermore the D3R HSP90 test compounds showed high structural similarity to existing HSP90 inhibitors in BindingDB. Thus, we adopted an integrated docking and scoring approach involving a combination of both pharmacophoric and heavy atom similarity alignments, local minimization and quantitative structure activity relationships modeling, resulting in the reasonable prediction of pose [with the root mean square deviation (RMSD) values of 1.75 Å for mean pose 1, 1.417 Å for the mean best pose and 1.85 Å for the mean all poses] and affinity (ROC AUC = 0.702 at 7.5 pIC50 cut-off and R = 0.45 for 180 compounds). The second protein, MAP4K4, represents a novel system with limited SAR and co-crystal structure data and little structural similarity of the D3R MAP4K4 test compounds to known MAP4K4 ligands. For this system, we implemented an exhaustive pose and affinity prediction protocol involving docking and scoring using the PLANTS software which considers side chain flexibility together with protein-ligand fingerprints analysis assisting in pose prioritization. This protocol through fares poorly in pose prediction (with the RMSD values of 4.346 Å for mean pose 1, 4.69 Å for mean best pose and 4.75 Å for mean all poses) and produced reasonable affinity prediction (AUC = 0.728 at 7.5 pIC50 cut-off and R = 0.67 for 18 compounds, ranked 1st among 80 submissions).

Paper-based immune-affinity arrays for detection of multiple mycotoxins in cereals.

PubMed

Li, Li; Chen, Hongpu; Lv, Xiaolan; Wang, Min; Jiang, Xizhi; Jiang, Yifei; Wang, Heye; Zhao, Yongfu; Xia, Liru

2018-03-01

Mycotoxins produced by different species of fungi may coexist in cereals and feedstuffs, and could be highly toxic for humans and animals. For quantification of multiple mycotoxins in cereals, we developed a paper-based mycotoxin immune-affinity array. First, paper-based microzone arrays were fabricated by photolithography. Then, monoclonal mycotoxin antibodies were added in a copolymerization reaction with a cross-linker to form an immune-affinity monolith on the paper-based microzone array. With use of a competitive immune-response format, paper-based mycotoxin immune-affinity arrays were successfully applied to detect mycotoxins in samples. The detection limits for deoxynivalenol, zearalenone, T-2 toxin, and HT-2 toxin were 62.7, 10.8, 0.36, and 0.23 μg·kg -1 , respectively, which meet relevant requirements for these compounds in food. The recovery rates were 81-86% for deoxynivalenol, 89-117% for zearalenone, 79-86% for T-2 toxin, and 78-83% for HT-2 toxin, and showed the paper-based immune-affinity arrays had good reproducibility. In summary, the paper-based mycotoxin immune-affinity array provides a sensitive, rapid, accurate, stable, and convenient platform for detection of multiple mycotoxins in agro-foods. Graphical abstract Paper-based immune-affinity monolithic array. DON deoxynivalenol, HT-2 HT-2 toxin, T-2 T-2 toxin, PEGDA polyethylene glycol diacrylate, ZEN zearalenone.

Trends in the phenotypic hip status of selected breeds of dog as measured by the New Zealand Veterinary Association Hip Dysplasia scheme (1990-2008).

PubMed

Worth, A J; Bridges, J P; Jones, G

2011-03-01

To determine whether there has been improvement in the phenotypic hip dysplasia status in four susceptible dog breeds as measured by the New Zealand Veterinary Association (NZVA) Canine Hip Dysplasia (CHD) scheme. A retrospective analysis of the NZVA CHD database was performed using records of all German Shepherd dogs, Labrador Retrievers, Golden Retrievers and Rottweilers that had undergone evaluation for hip dysplasia between 1990 and 2008. The effect of date of birth on the total hip score was analysed using linear regression, including the covariates of age and gender. When a significant effect of date of birth on total score was noted, ordinal logistic regression was performed to determine the probability of different grades of the Norberg angle and subluxation scores by year of birth; these categories being most indicative of laxity of the coxofemoral joint. Given the known heritability of hip phenotype, determined using radiological measurements, the hypothesis was that if sufficient selection pressure has been applied there would have been a trend towards a lower total score over time. For Labrador Retrievers (n=1,451), Golden Retrievers (n=896) and Rottweilers (n=313), there was no effect of date of birth on total score over the period of the study (p>0.1). For German Shepherd dogs (n=1,087), there was a significant trend to a lower total score over time (p=0.0003). However the actual size of the effect was small. Ordinal logistic regression on the Norberg angle and subluxation scores for German Shepherd dogs demonstrated a significant lowering of grade in both of these measures of hip laxity. This study failed to show significant improvement in the phenotypic hip status of three out of the four most populous large-dog breeds in the NZVA CHD database. Even in the German Shepherd dog, the trend towards a lower total score did not represent a substantial change. Lack of evidence of phenotypic improvement may be due to insufficient selection pressure over the course of the study, selective usage of the scheme (and thus a biased sample), or deficiencies within the NZVA CHD scoring method itself. Greater improvement might be possible if use of the scheme (or an equivalent) is made a compulsory requirement for registration of pedigree breeding stock, if greater selection pressure is applied and/or if pedigree data are included to enable estimations of breeding value.

Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.

PubMed

Holstein, Carly A; Chevalier, Aaron; Bennett, Steven; Anderson, Caitlin E; Keniston, Karen; Olsen, Cathryn; Li, Bing; Bales, Brian; Moore, David R; Fu, Elain; Baker, David; Yager, Paul

2016-02-01

To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.

Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

NASA Astrophysics Data System (ADS)

Singh, Sanjeev Kumar; Prasad, V. S.

2018-02-01

This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Understanding the basis of I50V-induced affinity decrease in HIV-1 protease via molecular dynamics simulations using polarized force field.

PubMed

Duan, Rui; Lazim, Raudah; Zhang, Dawei

2015-09-30

Human immunodeficiency virus (HIV)-1 protease is one of the most promising drug target commonly utilized to combat Acquired Immune Deficiency Syndrome (AIDS). However, with the emergence of drug resistance arising from mutations, the efficiency of protease inhibitors (PIs) as a viable treatment for AIDS has been greatly reduced. I50V mutation as one of the most significant mutations occurring in HIV-1 protease will be investigated in this study. Molecular dynamics (MD) simulation was utilized to examine the effect of I50V mutation on the binding of two PIs namely indinavir and amprenavir to HIV-1 protease. Prior to the simulations conducted, the electron density distributions of the PI and each residue in HIV-1 protease are derived by combining quantum fragmentation approach molecular fractionation with conjugate caps and Poisson-Boltzmann solvation model based on polarized protein-specific charge scheme. The atomic charges of the binding complex are subsequently fitted using delta restrained electrostatic potential (delta-RESP) method to overcome the poor charge determination of buried atom. This way, both intraprotease polarization and the polarization between protease and the PI are incorporated into partial atomic charges. Through this study, the mutation-induced affinity variations were calculated and significant agreement between experiments and MD simulations conducted was observed for both HIV-1 protease-drug complexes. In addition, the mechanism governing the decrease in the binding affinity of PI in the presence of I50V mutation was also explored to provide insights pertaining to the design of the next generation of anti-HIV drugs. © 2015 Wiley Periodicals, Inc.

Islands Unto Themselves: How Merit Pay Schemes May Undermine Positive Teacher Collaboration

ERIC Educational Resources Information Center

Brewer, T. Jameson; Myers, P. S.; Zhang, Michael

2015-01-01

Educational reforms have become the new policy mainstay in educational discourse and policy. Without doubt, "fixing" teachers and increasing student test scores have both been a large component of much of the reform rhetoric. Moreover, calls for implementing merit pay schemes have uniquely combined reformer's efforts to "fix"…

A novel method of assessing quality of postgraduate psychiatry training: experiences from a large training programme

PubMed Central

2013-01-01

Background Most assessments of the quality of postgraduate training are based on anonymised questionnaires of trainees. We report a comprehensive assessment of the quality of training at a large postgraduate psychiatry training institute using non-anonymised face-to-face interviews with trainees and their trainers. Methods Two consultant psychiatrists interviewed 99 trainees and 109 trainers. Scoring of interview responses was determined by using a pre-defined criteria. Additional comments were recorded as free text. Interviews covered 13 domains, including: Clinical, teaching, research and management opportunities, clinical environment, clinical supervision, adequacy of job description, absence of bullying and job satisfaction. Multiple interview domain scores were combined, generating a ‘Combined’ score for each post. Results The interview response rate was 97% for trainers 88% for trainees. There was a significant correlation between trainee and trainer scores for the same interview domains (Pearson’s r = 0.968, p< 0.001). Overall scores were significantly higher for specialist psychiatry posts as compared to general adult psychiatry posts (Two tailed t-test, p < 0.001, 95% CI: -0.398 to −0.132), and significantly higher for liaison psychiatry as compared to other specialist psychiatry posts (t-test: p = 0.038, 95% CI: -0.3901, -0.0118). Job satisfaction scores of year 1 to year 3 core trainees showed a significant increase with increasing seniority (Linear regression coefficient = 0.273, 95% CI: 0.033 to 0.513, ANOVA p= 0.026). Conclusions This in-depth examination of the quality of training on a large psychiatry training programme successfully elicited strengths and weakness of our programme. Such an interview scheme could be easily implemented in smaller schemes and may well provide important information to allow for targeted improvement of training. Additionally, trends in quality of training and job satisfaction amongst various psychiatric specialities were identified; specifically speciality posts and liaison posts in psychiatry were revealed to be the most popular with trainees. PMID:23768083

A novel method of assessing quality of postgraduate psychiatry training: experiences from a large training programme.

PubMed

Bizrah, Mukhtar; Iacoponi, Eduardo; Parker, Elizabeth; Rymer, Janice; Iversen, Amy; Wessely, Simon

2013-06-14

Most assessments of the quality of postgraduate training are based on anonymised questionnaires of trainees. We report a comprehensive assessment of the quality of training at a large postgraduate psychiatry training institute using non-anonymised face-to-face interviews with trainees and their trainers. Two consultant psychiatrists interviewed 99 trainees and 109 trainers. Scoring of interview responses was determined by using a pre-defined criteria. Additional comments were recorded as free text. Interviews covered 13 domains, including: Clinical, teaching, research and management opportunities, clinical environment, clinical supervision, adequacy of job description, absence of bullying and job satisfaction. Multiple interview domain scores were combined, generating a 'Combined' score for each post. The interview response rate was 97% for trainers 88% for trainees. There was a significant correlation between trainee and trainer scores for the same interview domains (Pearson's r = 0.968, p< 0.001). Overall scores were significantly higher for specialist psychiatry posts as compared to general adult psychiatry posts (Two tailed t-test, p < 0.001, 95% CI: -0.398 to -0.132), and significantly higher for liaison psychiatry as compared to other specialist psychiatry posts (t-test: p = 0.038, 95% CI: -0.3901, -0.0118). Job satisfaction scores of year 1 to year 3 core trainees showed a significant increase with increasing seniority (Linear regression coefficient = 0.273, 95% CI: 0.033 to 0.513, ANOVA p= 0.026). This in-depth examination of the quality of training on a large psychiatry training programme successfully elicited strengths and weakness of our programme. Such an interview scheme could be easily implemented in smaller schemes and may well provide important information to allow for targeted improvement of training. Additionally, trends in quality of training and job satisfaction amongst various psychiatric specialities were identified; specifically speciality posts and liaison posts in psychiatry were revealed to be the most popular with trainees.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

PubMed

Srinivasulu, Yerukala Sathipati; Wang, Jyun-Rong; Hsu, Kai-Ti; Tsai, Ming-Ju; Charoenkwan, Phasit; Huang, Wen-Lin; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes

PubMed Central

2015-01-01

Background Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. Results This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. Conclusions The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes. PMID:26681483

Structure guided inhibitor designing of CDK2 and discovery of potential leads against cancer.

PubMed

Kumar, Arun V A; Mohan, Keshav; Riyaz, Syed

2013-09-01

On the basis of stereo specific information obtained from crystal structures of CDK2, indole and chromene analogues were designed by suitably substituting the pharmacophores on their moiety and docked with target protein for calculating binding affinities. The binding affinities are represented in glide score. (5E)-5-[(1-methyl-1H-indol-3-yl)methylidene]-2,4,6-trioxotetrahydro-2H-pyrimidin-1-ide (I1), (5E)-5-(1H-indol-3-ylmethylidene)-2,4,6-trioxotetrahydro-2H-pyrimidin-1-ide (I2) and 2-amino-4-(4-methyl phenyl)-5-oxo-5,6,7,8-tetrahydro-4H-chromene-3-carbonitrile (C9) were selected for synthesis and biological testing based on vital interactions. (5E)-5-(1H-indol-3-ylmethylidene)-2,4,6-trioxotetrahydro-2H-pyrimidin-1-ide(I2) and 2-amino-4-(4-methyl phenyl)-5-oxo-5,6,7,8-tetrahydro-4H-chromene-3-carbonitrile (C9) were proved to be active against MCF-7 and HeLa cell lines.

Performance of Clinical Laboratories in South African Parasitology Proficiency Testing Surveys between 2004 and 2010

PubMed Central

Dini, Leigh; Frean, John

2012-01-01

Performance in proficiency testing (PT) schemes is an objective measure of a laboratory's best performance. We examined the performance of participants in two parasitology PT schemes in South Africa from 2004 through 2010. The average rates of acceptable scores over the period were 58% and 66% for the stool and blood parasite schemes, respectively. In our setting, participation in PT alone is insufficient to improve performance; a policy that provides additional resources and training seems necessary. PMID:22814470

RAS screening in colorectal cancer: a comprehensive analysis of the results from the UK NEQAS colorectal cancer external quality assurance schemes (2009-2016).

PubMed

Richman, Susan D; Fairley, Jennifer; Butler, Rachel; Deans, Zandra C

2017-12-01

Evidence strongly indicates that extended RAS testing should be undertaken in mCRC patients, prior to prescribing anti-EGFR therapies. With more laboratories implementing testing, the requirement for External Quality Assurance schemes increases, thus ensuring high standards of molecular analysis. Data was analysed from 15 United Kingdom National External Quality Assessment Service (UK NEQAS) for Molecular Genetics Colorectal cancer external quality assurance (EQA) schemes, delivered between 2009 and 2016. Laboratories were provided annually with nine colorectal tumour samples for genotyping. Information on methodology and extent of testing coverage was requested, and scores given for genotyping, interpretation and clerical accuracy. There has been a sixfold increase in laboratory participation (18 in 2009 to 108 in 2016). For RAS genotyping, fewer laboratories now use Roche cobas®, pyrosequencing and Sanger sequencing, with more moving to next generation sequencing (NGS). NGS is the most commonly employed technology for BRAF and PIK3CA mutation screening. KRAS genotyping errors were seen in ≤10% laboratories, until the 2014-2015 scheme, when there was an increase to 16.7%, corresponding to a large increase in scheme participants. NRAS genotyping errors peaked at 25.6% in the first 2015-2016 scheme but subsequently dropped to below 5%. Interpretation and clerical accuracy scores have been consistently good throughout. Within this EQA scheme, we have observed that the quality of molecular analysis for colorectal cancer has continued to improve, despite changes in the required targets, the volume of testing and the technologies employed. It is reassuring to know that laboratories clearly recognise the importance of participating in EQA schemes.

Transient times in linear metabolic pathways under constant affinity constraints.

PubMed

Lloréns, M; Nuño, J C; Montero, F

1997-10-15

In the early seventies, Easterby began the analytical study of transition times for linear reaction schemes [Easterby (1973) Biochim. Biophys. Acta 293, 552-558]. In this pioneer work and in subsequent papers, a state function (the transient time) was used to measure the period before the stationary state, for systems constrained to work under both constant and variable input flux, was reached. Despite the undoubted usefulness of this quantity to describe the time-dependent features of these kinds of systems, its application to the study of chemical reactions under other constraints is questionable. In the present work, a generalization of these magnitudes to linear metabolic pathways functioning under a constant-affinity constraint is carried out. It is proved that classical definitions of transient times do not reflect the actual properties of the transition to the steady state in systems evolving under this restriction. Alternatively, a more adequate framework for interpretation of the transient times for systems with both constant and variable input flux is suggested. Within this context, new definitions that reflect more accurately the transient characteristics of constant affinity systems are stated. Finally, the meaning of these transient times is discussed.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

Molecular modeling and dynamics simulations of PNP from Streptococcus agalactiae.

PubMed

Caceres, Rafael Andrade; Saraiva Timmers, Luis Fernando; Dias, Raquel; Basso, Luiz Augusto; Santos, Diogenes Santiago; de Azevedo, Walter Filgueira

2008-05-01

This work describes for the first time a structural model of purine nucleoside phosphorylase from Streptococcus agalactiae (SaPNP). PNP catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is a potential target for the development of antibacterial drugs. We modeled the complexes of SaPNP with 15 different ligands in order to determine the structural basis for the specificity of these ligands against SaPNP. The application of a novel empirical scoring function to estimate the affinity of a ligand for a protein was able to identify the ligands with high affinity for PNPs. The analysis of molecular dynamics trajectory for SaPNP indicates that the functionally important motifs have a very stable structure. This new structural model together with a novel empirical scoring function opens the possibility to explorer larger library of compounds in order to identify the new inhibitors for PNPs in virtual screening projects.

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

PubMed

Lee, Hui Sun; Jo, Sunhwan; Lim, Hyun-Suk; Im, Wonpil

2012-07-23

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein's structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions.

NMRe: a web server for NMR protein structure refinement with high-quality structure validation scores.

PubMed

Ryu, Hyojung; Lim, GyuTae; Sung, Bong Hyun; Lee, Jinhyuk

2016-02-15

Protein structure refinement is a necessary step for the study of protein function. In particular, some nuclear magnetic resonance (NMR) structures are of lower quality than X-ray crystallographic structures. Here, we present NMRe, a web-based server for NMR structure refinement. The previously developed knowledge-based energy function STAP (Statistical Torsion Angle Potential) was used for NMRe refinement. With STAP, NMRe provides two refinement protocols using two types of distance restraints. If a user provides NOE (Nuclear Overhauser Effect) data, the refinement is performed with the NOE distance restraints as a conventional NMR structure refinement. Additionally, NMRe generates NOE-like distance restraints based on the inter-hydrogen distances derived from the input structure. The efficiency of NMRe refinement was validated on 20 NMR structures. Most of the quality assessment scores of the refined NMR structures were better than those of the original structures. The refinement results are provided as a three-dimensional structure view, a secondary structure scheme, and numerical and graphical structure validation scores. NMRe is available at http://psb.kobic.re.kr/nmre/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

Radar-derived quantitative precipitation estimation in complex terrain over the eastern Tibetan Plateau

NASA Astrophysics Data System (ADS)

Gou, Yabin; Ma, Yingzhao; Chen, Haonan; Wen, Yixin

2018-05-01

Quantitative precipitation estimation (QPE) is one of the important applications of weather radars. However, in complex terrain such as Tibetan Plateau, it is a challenging task to obtain an optimal Z-R relation due to the complex spatial and temporal variability in precipitation microphysics. This paper develops two radar QPE schemes respectively based on Reflectivity Threshold (RT) and Storm Cell Identification and Tracking (SCIT) algorithms using observations from 11 Doppler weather radars and 3264 rain gauges over the Eastern Tibetan Plateau (ETP). These two QPE methodologies are evaluated extensively using four precipitation events that are characterized by different meteorological features. Precipitation characteristics of independent storm cells associated with these four events, as well as the storm-scale differences, are investigated using short-term vertical profile of reflectivity (VPR) clusters. Evaluation results show that the SCIT-based rainfall approach performs better than the simple RT-based method for all precipitation events in terms of score comparison using validation gauge measurements as references. It is also found that the SCIT-based approach can effectively mitigate the local error of radar QPE and represent the precipitation spatiotemporal variability better than the RT-based scheme.

Transferon™, a peptide mixture with immunomodulatory properties is not immunogenic when administered with various adjuvants.

PubMed

Avila, Sandra; Muñoz-García, Leslie; Vázquez-Leyva, Said; Salinas-Jazmín, Nohemí; Medina-Rivero, Emilio; Pavón, Lenin; Mellado-Sánchez, Gabriela; Chacón-Salinas, Rommel; Estrada-Parra, Sergio; Vallejo-Castillo, Luis; Pérez-Tapia, Sonia Mayra

2017-12-01

Transferon, a human dialyzable leukocyte extract (hDLE), is a biotherapeutic that comprises a complex mixture of low-molecular-weight peptides (< 10 kDa) and is used to treat diseases with an inflammatory component. Some biotherapeutics, including those composed of peptides, can induce anti-drug antibodies (ADA) that block or diminish their therapeutic effect. Nevertheless, few studies have evaluated peptide-derived drug immunogenicity. In this study, the immunogenicity of Transferon was examined in a murine model during an immunization scheme using the following adjuvants: Al(OH) 3 , incomplete Freund's adjuvant (IFA), or Titermax Gold. The inoculation scheme entailed three routes of administration (intraperitoneal, Day 1; subcutaneous, Day 7; and intramuscular, Day 14) using 200 μg Transferon/inoculation. Serum samples were collected on Day 21. Total IgG levels were quantitated by affinity chromatography, and specific antibodies against components of Transferon were analyzed by dot-blot and ELISA. Ovalbumin (OVA, 44 kDa) and peptides from hydrolyzed collagen (PFHC, < 17 kDa) were used as positive and negative controls, respectively, in the same inoculation scheme and analyses for Transferon. OVA, PFHC, and Transferon increased total IgG concentrations in mice. However, only IgG antibodies against OVA were detected. Based on the results, it is concluded that Transferon does not induce generation of specific antibodies against its components in this model, regardless of adjuvant and route of administration. These results support the safety of Transferon by confirming its inability to induce ADA in this animal model.

Relevance popularity: A term event model based feature selection scheme for text classification.

PubMed

Feng, Guozhong; An, Baiguo; Yang, Fengqin; Wang, Han; Zhang, Libiao

2017-01-01

Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis.

PubMed

Liu, Gang; Cheng, Kai; Lo, Chi Y; Li, Jun; Qu, Jun; Neelamegham, Sriram

2017-11-01

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MS n proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MS n data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MS n spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction

NASA Astrophysics Data System (ADS)

Sulea, Traian; Hogues, Hervé; Purisima, Enrico O.

2012-05-01

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host-guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.

Face-iris multimodal biometric scheme based on feature level fusion

NASA Astrophysics Data System (ADS)

Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

2015-11-01

Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

Assessment of three medical and research laboratories using WHO AFRO_SLIPTA Quality Standards in Southwestern Uganda: a long way to go.

PubMed

Taremwa, Ivan Mugisha; Ampaire, Lucas; Iramiot, Jacob; Muhwezi, Obed; Matte, Aloysius; Itabangi, Herbert; Mbabazi, Hope; Atwebembeire, Jeninah; Kamwine, Monicah; Katawera, Victoria; Mbalibulha, Yona; Orikiriza, Patrick; Boum, Yap

2017-01-01

While the laboratory represents more than 70% of clinical diagnosis and patient management, access to reliable and quality laboratory diagnostics in sub-Saharan Africa remains a challenge. To gain knowledge and suggest evidence based interventions towards laboratory improvement in Southwestern Uganda, we assessed the baseline laboratory quality standards in three medical and research laboratories in Southwestern Uganda. We conducted a cross sectional survey from October, 2013 to April, 2014. Selected laboratories, including one private research, one private for profit and one public laboratory, were assessed using the WHO AFRO_SLIPTA checklist and baseline scores were determined. The three laboratories assessed met basic facility requirements, had trained personnel, and safety measures in place. Sample reception was properly designed and executed with a well designated chain of custody. All laboratories had sufficient equipment for the nature of work they were involved in. However, we found that standard operating procedures were incomplete in all three laboratories, lack of quality audit schemes by two laboratories and only one laboratory enrolled into external quality assurance schemes. The SLIPTA scores were one star for the research laboratory and no star for both the public and private-for-profit laboratories. While most of the laboratory systems were in place, the low scores obtained by the assessed laboratories reflect the need for improvement to reach standards of quality assured diagnostics in the region. Therefore, routine mentorship and regional supportive supervision are necessary to increase the quality of laboratory services.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Synthesis, molecular properties estimations, and dual dopamine D2 and D3 receptor activities of Benzthiazole-based ligands.

NASA Astrophysics Data System (ADS)

Schübler, Moritz; Sadek, Bassem; Kottke, Tim; Weizel, Lilia; Stark, Holger

2017-09-01

Neurleptic drugs, e.g. aripiprazole, targeting the dopamine D2s and D3 receptors (D2sR and D3R) in the central nervous system are widely used in the treatment of several psychotic and neurodegenerative diseases. Therefore, a new series of benz[d]thiazole-based ligands (1-18) was synthesized by applying the bioisosteric approach derived from the selective D3Rs ligand BP-897 and its structurally related benz[d]imidazole derivatives. Herein, introduction of the benz[d]thiazole moiety was well tolerated by D2sR and D3R binding sites leading to antagonist affinities in the low nanomolar concentration range at both receptor subtypes. Further exploration of different substitution patterns at the benz[d]thiazole heterocycle and the basic 4-phenylpiperazine resulted in the discovery of high dually acting D2sR and D3R ligands. Moreover, the methoxy substitution at 2-position of 4-phenylpiperazine resulted in significantly (22-fold) increased D2sR binding affinity as compared to the parent ligand BP-897, and improved physicochemical and drug-likeness properties of ligands 1-9. However, the latter structural modifications failed to improve the drug-able properties in ligands having un-substituted 4-phenylpiperazine analogues (10-18). Accordingly, compound 7 showed in addition to high dual affinity at the D2sR and D3R (Ki (hD2SR) = 2.8 ± 0.8 nM; Ki (hD3R) = 3.0 ± 1.6 nM), promising clogS, clogP, LE (hD2sR, hD3R), LipE (hD2sR, hD3R), and drug-likeness score values of -4.7, 4.2, (0.4, 0.4), (4.4, 4.3), and 0.7, respectively. Also, the deaminated analogue 8 (Ki (hD2SR) = 3.2 ± 0.4 nM; Ki (hD3R) = 8.5 ± 2.2 nM) revealed clogS, clogP, LE (hD2sR, hD3R), LipE (hD2sR, hD3R) and drug-likeness score values of -4.7, 4.2, (0.4, 0.4), (3.9, 3.5), and 0.4, respectively. The results observed for the newly developed benz[d]thiazole-based ligands 1-18 provide clues for the diversity in structure activity relationships (SARs) at the D2sR and D3R subtypes.

[Optimization of acupoint application scheme in the treatment of bronchial asthma based on the orthogonal design method].

PubMed

Shi, Kuan; Wu, Wenzhong; Liu, Lanying; Wang, Hesheng; Chen, Dong; Liu, Chengyong; Zhang, Cong

2017-06-12

To study the primary and secondary factors of the allergic history, the frequency of acupoint application and the time of acupoint application in the treatment of bronchial asthma and optimize its scheme. Eighty patients of bronchial asthma were selected as the subjects in the orthogonal trial. The herbal medicines were the empirical formula of acupoint application (prepared at the ratio as 2:2:1:1:1:1:1:1:1 of semen brassicae , rhizome corydalis , unprocessed radix kansui , asarum sieboldii , ephedra , semen lepidii , syzygium aromaticum , cortex cinnamomi and fructus gleditsiae ) and used on bilateral Feishu (BL 13), Xinshu (BL 15), Geshu (BL 17) and Shenshu (BL 23). Firstly, two groups were divided according to allergic history (40 cases with allergic history and 40 cases without allergic history), and then four subgroups were divided on the basis of the two main groups, 10 cases in each one. Through studying three factors and two levels, i.e. allergic history (Factor A:A Ⅰ :with allergic history; A Ⅱ :without allergic history), the frequency of acupoint application (Factor B:B Ⅰ :4 times; B Ⅱ :10 times, in which, in the group of 4-time applications, the application was given once every 10 days; in the group of 10-time applications, the application was given once every 4 days); and the time of application (Factor C:C Ⅰ :4 h; C Ⅱ :8 h), the optimal scheme was screened on the basis of the attack frequency before and after treatment and the score of the asthma quality life questionnaire (AQLQ) before treatment and 6 months after treatment in the patients of each group. ① The orthogonal trial indicated that the best optimal scheme was A Ⅰ B Ⅱ C Ⅰ , meaning the patients with allergic history were treated with acupoint application for 10 times, remained for 4 h. ②Factor B (frequency of acupoint application) and C (time of acpoint application) were the significant influential factors of AQLQ scores (both P <0.05). ③The comparison of the attack frequency and AQLQ score before and after treatment in all of the patients showed that the different combinations of factor levels induced the different impacts on the asthma attack frequency and AQLQ scores. Except in the group No.1 and the group No.5, the improvements were all significant in the rest groups, indicating the significant differences ( P <0.05, P <0.01). Acupoint application reduces apparently the attack frequency of asthma in the patients and improves the living quality. The primary and secondary relationship among the allergic history, the frequency of acupoint application and the time of acupoint application for the impacts on the therapeutic effects are:the frequency of acupoint application > the time of acupoint application > the allergic history. The best optimal scheme is A Ⅰ B Ⅱ C Ⅰ , meaning the patients with allergic history are treated with acupoint application for 10 times, remained for 4h.

An interlaboratory comparison programme on radio frequency electromagnetic field measurements: the second round of the scheme.

PubMed

Nicolopoulou, E P; Ztoupis, I N; Karabetsos, E; Gonos, I F; Stathopulos, I A

2015-04-01

The second round of an interlaboratory comparison scheme on radio frequency electromagnetic field measurements has been conducted in order to evaluate the overall performance of laboratories that perform measurements in the vicinity of mobile phone base stations and broadcast antenna facilities. The participants recorded the electric field strength produced by two high frequency signal generators inside an anechoic chamber in three measurement scenarios with the antennas transmitting each time different signals at the FM, VHF, UHF and GSM frequency bands. In each measurement scenario, the participants also used their measurements in order to calculate the relative exposure ratios. The results were evaluated in each test level calculating performance statistics (z-scores and En numbers). Subsequently, possible sources of errors for each participating laboratory were discussed, and the overall evaluation of their performances was determined by using an aggregated performance statistic. A comparison between the two rounds proves the necessity of the scheme. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Piezoelectric tuning fork biosensors for the quantitative measurement of biomolecular interactions

NASA Astrophysics Data System (ADS)

Gonzalez, Laura; Rodrigues, Mafalda; Benito, Angel Maria; Pérez-García, Lluïsa; Puig-Vidal, Manel; Otero, Jorge

2015-12-01

The quantitative measurement of biomolecular interactions is of great interest in molecular biology. Atomic force microscopy (AFM) has proved its capacity to act as a biosensor and determine the affinity between biomolecules of interest. Nevertheless, the detection scheme presents certain limitations when it comes to developing a compact biosensor. Recently, piezoelectric quartz tuning forks (QTFs) have been used as laser-free detection sensors for AFM. However, only a few studies along these lines have considered soft biological samples, and even fewer constitute quantified molecular recognition experiments. Here, we demonstrate the capacity of QTF probes to perform specific interaction measurements between biotin-streptavidin complexes in buffer solution. We propose in this paper a variant of dynamic force spectroscopy based on representing adhesion energies E (aJ) against pulling rates v (nm s-1). Our results are compared with conventional AFM measurements and show the great potential of these sensors in molecular interaction studies.

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

PubMed

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

What the "Overall" Doesn't Tell about World University Rankings: Examples from ARWU, QSWUR, and THEWUR in 2013

ERIC Educational Resources Information Center

Soh, Kaycheng

2015-01-01

In the various world university ranking schemes, the "Overall" is a sum of the weighted indicator scores. As the indicators are of a different nature from each other, "Overall" conceals important differences. Factor analysis of the data from three prominent ranking schemes reveals that there are two factors in each of the…

Heritability and phenotypic variation of canine hip dysplasia radiographic traits in a cohort of Australian German shepherd dogs.

PubMed

Wilson, Bethany J; Nicholas, Frank W; James, John W; Wade, Claire M; Tammen, Imke; Raadsma, Herman W; Castle, Kao; Thomson, Peter C

2012-01-01

Canine Hip Dysplasia (CHD) is a common, painful and debilitating orthopaedic disorder of dogs with a partly genetic, multifactorial aetiology. Worldwide, potential breeding dogs are evaluated for CHD using radiographically based screening schemes such as the nine ordinally-scored British Veterinary Association Hip Traits (BVAHTs). The effectiveness of selective breeding based on screening results requires that a significant proportion of the phenotypic variation is caused by the presence of favourable alleles segregating in the population. This proportion, heritability, was measured in a cohort of 13,124 Australian German Shepherd Dogs born between 1976 and 2005, displaying phenotypic variation for BVAHTs, using ordinal, linear and binary mixed models fitted by a Restricted Maximum Likelihood method. Heritability estimates for the nine BVAHTs ranged from 0.14-0.24 (ordinal models), 0.14-0.25 (linear models) and 0.12-0.40 (binary models). Heritability for the summed BVAHT phenotype was 0.30 ± 0.02. The presence of heritable variation demonstrates that selection based on BVAHTs has the potential to improve BVAHT scores in the population. Assuming a genetic correlation between BVAHT scores and CHD-related pain and dysfunction, the welfare of Australian German Shepherds can be improved by continuing to consider BVAHT scores in the selection of breeding dogs, but that as heritability values are only moderate in magnitude the accuracy, and effectiveness, of selection could be improved by the use of Estimated Breeding Values in preference to solely phenotype based selection of breeding animals.

Searching for DNA Lesions: Structural Evidence for Lower- and Higher-Affinity DNA Binding Conformations of Human Alkyladenine DNA Glycosylase

PubMed Central

2011-01-01

To efficiently repair DNA, human alkyladenine DNA glycosylase (AAG) must search the million-fold excess of unmodified DNA bases to find a handful of DNA lesions. Such a search can be facilitated by the ability of glycosylases, like AAG, to interact with DNA using two affinities: a lower-affinity interaction in a searching process and a higher-affinity interaction for catalytic repair. Here, we present crystal structures of AAG trapped in two DNA-bound states. The lower-affinity depiction allows us to investigate, for the first time, the conformation of this protein in the absence of a tightly bound DNA adduct. We find that active site residues of AAG involved in binding lesion bases are in a disordered state. Furthermore, two loops that contribute significantly to the positive electrostatic surface of AAG are disordered. Additionally, a higher-affinity state of AAG captured here provides a fortuitous snapshot of how this enzyme interacts with a DNA adduct that resembles a one-base loop. PMID:22148158

Introducing Large-Scale Innovation in Schools

NASA Astrophysics Data System (ADS)

Sotiriou, Sofoklis; Riviou, Katherina; Cherouvis, Stephanos; Chelioti, Eleni; Bogner, Franz X.

2016-08-01

Education reform initiatives tend to promise higher effectiveness in classrooms especially when emphasis is given to e-learning and digital resources. Practical changes in classroom realities or school organization, however, are lacking. A major European initiative entitled Open Discovery Space (ODS) examined the challenge of modernizing school education via a large-scale implementation of an open-scale methodology in using technology-supported innovation. The present paper describes this innovation scheme which involved schools and teachers all over Europe, embedded technology-enhanced learning into wider school environments and provided training to teachers. Our implementation scheme consisted of three phases: (1) stimulating interest, (2) incorporating the innovation into school settings and (3) accelerating the implementation of the innovation. The scheme's impact was monitored for a school year using five indicators: leadership and vision building, ICT in the curriculum, development of ICT culture, professional development support, and school resources and infrastructure. Based on about 400 schools, our study produced four results: (1) The growth in digital maturity was substantial, even for previously high scoring schools. This was even more important for indicators such as vision and leadership" and "professional development." (2) The evolution of networking is presented graphically, showing the gradual growth of connections achieved. (3) These communities became core nodes, involving numerous teachers in sharing educational content and experiences: One out of three registered users (36 %) has shared his/her educational resources in at least one community. (4) Satisfaction scores ranged from 76 % (offer of useful support through teacher academies) to 87 % (good environment to exchange best practices). Initiatives such as ODS add substantial value to schools on a large scale.

A new approach to develop computer-aided detection schemes of digital mammograms

NASA Astrophysics Data System (ADS)

Tan, Maxine; Qian, Wei; Pu, Jiantao; Liu, Hong; Zheng, Bin

2015-06-01

The purpose of this study is to develop a new global mammographic image feature analysis based computer-aided detection (CAD) scheme and evaluate its performance in detecting positive screening mammography examinations. A dataset that includes images acquired from 1896 full-field digital mammography (FFDM) screening examinations was used in this study. Among them, 812 cases were positive for cancer and 1084 were negative or benign. After segmenting the breast area, a computerized scheme was applied to compute 92 global mammographic tissue density based features on each of four mammograms of the craniocaudal (CC) and mediolateral oblique (MLO) views. After adding three existing popular risk factors (woman’s age, subjectively rated mammographic density, and family breast cancer history) into the initial feature pool, we applied a sequential forward floating selection feature selection algorithm to select relevant features from the bilateral CC and MLO view images separately. The selected CC and MLO view image features were used to train two artificial neural networks (ANNs). The results were then fused by a third ANN to build a two-stage classifier to predict the likelihood of the FFDM screening examination being positive. CAD performance was tested using a ten-fold cross-validation method. The computed area under the receiver operating characteristic curve was AUC = 0.779   ±   0.025 and the odds ratio monotonically increased from 1 to 31.55 as CAD-generated detection scores increased. The study demonstrated that this new global image feature based CAD scheme had a relatively higher discriminatory power to cue the FFDM examinations with high risk of being positive, which may provide a new CAD-cueing method to assist radiologists in reading and interpreting screening mammograms.

A comparative approach to the study of Keeper-Animal Relationships in the zoo.

PubMed

Carlstead, Kathy

2009-11-01

Research on intensively farmed animals over the past 25 years has shown that human-animal interactions, by affecting the animal's fear of humans, can markedly limit the productivity and welfare of farm animals. This article begins to explore some of the factors that need to be considered to investigate Keeper-Animal Relationships (KARs) in the zoo. In the mid-1990s, a large body of multi-institutional data on zookeepers and animals was collected from 46 Zoos. Using standardized questionnaires, 82 keepers rated how they behaved towards animals, their husbandry routine, how the animal responds to them and to other people, and provided information about themselves. These data include 219 individuals of four endangered species: black rhinoceros, cheetah, maned wolf, and great hornbill. At each zoo, keepers were also videotaped calling to their animals in order to directly observe animal responses to keeper behaviors. Principle Components Analysis reduced eight animal variables to three components and ten keeper variables to five components. Scores for animals and for keepers were calculated on these components and compared, according to five predictions based on models of human-animal interactions in the literature. Animal responses to keepers varied along three dimensions: Affinity to Keeper, Fear of People, and Sociable/Curious. Animal scores of Fear of People were significantly and positively correlated with independent measures of poor welfare from two later studies: fecal corticoid concentrations for 12 black rhinos and "tense-fearful" scores for 12 cheetahs. (1) Significant species differences were found for Affinity to Keeper and Fear of People, and the interaction of these two dimensions of animal response to keepers appears to be species-specific. (2) The quality of KAR is influenced by whether the zookeeper goes in the enclosure with the animal or not, the frequency and time of feeding, and keeper visibility to the animal. Among keepers who go in with their animals, a significant negative correlation between Frequency of Feeding/Early Feedtime and average Affinity to Keeper of their animals, and a positive correlation between Keeper Experience and their animals' Fear of People, indicates that certain zoo keeping styles or habits among experienced keepers might be aversive and increase fear among animals. (3) Keepers who locomote or make unexpected noises when calling their animals elicit increased aggression or apprehension from maned wolves and cheetahs. (4) Wild-born black rhino and parent-reared maned wolf have significantly less affinity to keepers than their captive-born or hand-reared counterparts, but neither differs in Fear of People. (5) Keeper-animal relationships are likely to be reciprocal as evidenced by a negative correlation of Job Satisfaction with animal Fear of People. Future research directions are discussed with respect to assessment of keeper attitudes and behaviors, animal fear, positive measures of welfare, and positive reinforcement training.

Virtual screening of ABCC1 transporter nucleotidebinding domains as a therapeutic target in multidrug resistant cancer

PubMed Central

Rungsardthong, Kanin; Mares- Sámano, Sergio; Penny, Jeffrey

2012-01-01

ABCC1 is a member of the ATP-binding Cassette super family of transporters, actively effluxes xenobiotics from cells. Clinically, ABCC1 expression is linked to cancer multidrug resistance. Substrate efflux is energised by ATP binding and hydrolysis at the nucleotide-binding domains (NBDs) and inhibition of these events may help combat drug resistance. The aim of this study is to identify potential inhibitors of ABCC1 through virtual screening of National Cancer Institute (NCI) compounds. A threedimensional model of ABCC1 NBD2 was generated using MODELLER whilst the X-ray crystal structure of ABCC1 NBD1 was retrieved from the Protein Data Bank. A pharmacophore hypothesis was generated based on flavonoids known to bind at the NBDs using PHASE, and used to screen the NCI database. GLIDE was employed in molecular docking studies for all hit compounds identified by pharmacophore screening. The best potential inhibitors were identified as compounds possessing predicted binding affinities greater than ATP. Approximately 5% (13/265) of the hit compounds possessed lower docking scores than ATP in ABCC1 NBD1 (NSC93033, NSC662377, NSC319661, NSC333748, NSC683893, NSC226639, NSC94231, NSC55979, NSC169121, NSC166574, NSC73380, NSC127738, NSC115534), whereas approximately 7% (7/104) of docked NCI compounds were predicted to possess lower docking scores than ATP in ABCC1 NBD2 (NSC91789, NSC529483, NSC211168, NSC318214, NSC116519, NSC372332, NSC526974). Analyses of docking orientations revealed P-loop residues of each NBD and the aromatic amino acids Trp653 (NBD1) and Tyr1302 (NBD2) were key in interacting with high-affinity compounds. On the basis of docked orientation and docking score the compounds identified may be potential inhibitors of ABCC1 and require further pharmacological analysis. Abbreviations ABC - ATP-binding cassette, DHS - dehydrosilybin, MDR - multidrug resistance, NBD - nucleotide-binding domain, PDB - protein data bank. PMID:23144549

Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

NASA Astrophysics Data System (ADS)

Galperin, Michael

2003-05-01

A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.

Methyl cation affinities of neutral and anionic maingroup-element hydrides: trends across the periodic table and correlation with proton affinities.

PubMed

Mulder, R Joshua; Guerra, Célia Fonseca; Bickelhaupt, F Matthias

2010-07-22

We have computed the methyl cation affinities in the gas phase of archetypal anionic and neutral bases across the periodic table using ZORA-relativistic density functional theory (DFT) at BP86/QZ4P//BP86/TZ2P. The main purpose of this work is to provide the methyl cation affinities (and corresponding entropies) at 298 K of all anionic (XH(n-1)(-)) and neutral bases (XH(n)) constituted by maingroup-element hydrides of groups 14-17 and the noble gases (i.e., group 18) along the periods 2-6. The cation affinity of the bases decreases from H(+) to CH(3)(+). To understand this trend, we have carried out quantitative bond energy decomposition analyses (EDA). Quantitative correlations are established between the MCA and PA values.

Narrative Skills in Young Adults with High-Functioning Autism Spectrum Disorders

ERIC Educational Resources Information Center

Rollins, Pamela Rosenthal

2014-01-01

In this study, the author investigated narrative performances of 10 high-functioning young adults with Autism Spectrum Disorders (ASD) across personal and storybook narratives. Narratives were elicited with genre-specific procedures and then transcribed and scored using the narrative scoring scheme (NSS). One-tailed paired-sample t tests were…

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

PubMed

Brylinski, Michal

2013-11-25

A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely available to the academic community as a Web server at http://www.brylinski.org/esimdock .

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Optimal rotated staggered-grid finite-difference schemes for elastic wave modeling in TTI media

NASA Astrophysics Data System (ADS)

Yang, Lei; Yan, Hongyong; Liu, Hong

2015-11-01

The rotated staggered-grid finite-difference (RSFD) is an effective approach for numerical modeling to study the wavefield characteristics in tilted transversely isotropic (TTI) media. But it surfaces from serious numerical dispersion, which directly affects the modeling accuracy. In this paper, we propose two different optimal RSFD schemes based on the sampling approximation (SA) method and the least-squares (LS) method respectively to overcome this problem. We first briefly introduce the RSFD theory, based on which we respectively derive the SA-based RSFD scheme and the LS-based RSFD scheme. Then different forms of analysis are used to compare the SA-based RSFD scheme and the LS-based RSFD scheme with the conventional RSFD scheme, which is based on the Taylor-series expansion (TE) method. The contrast in numerical accuracy analysis verifies the greater accuracy of the two proposed optimal schemes, and indicates that these schemes can effectively widen the wavenumber range with great accuracy compared with the TE-based RSFD scheme. Further comparisons between these two optimal schemes show that at small wavenumbers, the SA-based RSFD scheme performs better, while at large wavenumbers, the LS-based RSFD scheme leads to a smaller error. Finally, the modeling results demonstrate that for the same operator length, the SA-based RSFD scheme and the LS-based RSFD scheme can achieve greater accuracy than the TE-based RSFD scheme, while for the same accuracy, the optimal schemes can adopt shorter difference operators to save computing time.

Computerized quantitative evaluation of mammographic accreditation phantom images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Yongbum; Tsai, Du-Yih; Shinohara, Norimitsu

2010-12-15

Purpose: The objective was to develop and investigate an automated scoring scheme of the American College of Radiology (ACR) mammographic accreditation phantom (RMI 156, Middleton, WI) images. Methods: The developed method consisted of background subtraction, determination of region of interest, classification of fiber and mass objects by Mahalanobis distance, detection of specks by template matching, and rule-based scoring. Fifty-one phantom images were collected from 51 facilities for this study (one facility provided one image). A medical physicist and two radiologic technologists also scored the images. The human and computerized scores were compared. Results: In terms of meeting the ACR's criteria,more » the accuracies of the developed method for computerized evaluation of fiber, mass, and speck were 90%, 80%, and 98%, respectively. Contingency table analysis revealed significant association between observer and computer scores for microcalcifications (p<5%) but not for masses and fibers. Conclusions: The developed method may achieve a stable assessment of visibility for test objects in mammographic accreditation phantom image in whether the phantom image meets the ACR's criteria in the evaluation test, although there is room left for improvement in the approach for fiber and mass objects.« less

Ethnicity identification from face images

NASA Astrophysics Data System (ADS)

Lu, Xiaoguang; Jain, Anil K.

2004-08-01

Human facial images provide the demographic information, such as ethnicity and gender. Conversely, ethnicity and gender also play an important role in face-related applications. Image-based ethnicity identification problem is addressed in a machine learning framework. The Linear Discriminant Analysis (LDA) based scheme is presented for the two-class (Asian vs. non-Asian) ethnicity classification task. Multiscale analysis is applied to the input facial images. An ensemble framework, which integrates the LDA analysis for the input face images at different scales, is proposed to further improve the classification performance. The product rule is used as the combination strategy in the ensemble. Experimental results based on a face database containing 263 subjects (2,630 face images, with equal balance between the two classes) are promising, indicating that LDA and the proposed ensemble framework have sufficient discriminative power for the ethnicity classification problem. The normalized ethnicity classification scores can be helpful in the facial identity recognition. Useful as a "soft" biometric, face matching scores can be updated based on the output of ethnicity classification module. In other words, ethnicity classifier does not have to be perfect to be useful in practice.

Robust wafer identification recognition based on asterisk-shape filter and high-low score comparison method.

PubMed

Hsu, Wei-Chih; Yu, Tsan-Ying; Chen, Kuan-Liang

2009-12-10

Wafer identifications (wafer ID) can be used to identify wafers from each other so that wafer processing can be traced easily. Wafer ID recognition is one of the problems of optical character recognition. The process to recognize wafer IDs is similar to that used in recognizing car license-plate characters. However, due to some unique characteristics, such as the irregular space between two characters and the unsuccessive strokes of wafer ID, it will not get a good result to recognize wafer ID by directly utilizing the approaches used in car license-plate character recognition. Wafer ID scratches are engraved by a laser scribe almost along the following four fixed directions: horizontal, vertical, plus 45 degrees , and minus 45 degrees orientations. The closer to the center line of a wafer ID scratch, the higher the gray level will be. These and other characteristics increase the difficulty to recognize the wafer ID. In this paper a wafer ID recognition scheme based on an asterisk-shape filter and a high-low score comparison method is proposed to cope with the serious influence of uneven luminance and make recognition more efficiently. Our proposed approach consists of some processing stages. Especially in the final recognition stage, a template-matching method combined with stroke analysis is used as a recognizing scheme. This is because wafer IDs are composed of Semiconductor Equipment and Materials International (SEMI) standard Arabic numbers and English alphabets, and thus the template ID images are easy to obtain. Furthermore, compared with the approach that requires prior training, such as a support vector machine, which often needs a large amount of training image samples, no prior training is required for our approach. The testing results show that our proposed scheme can efficiently and correctly segment out and recognize the wafer ID with high performance.

BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

PubMed

Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

2016-10-01

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study.

PubMed

Hassan, Mubashir; Abbas, Qamar; Ashraf, Zaman; Moustafa, Ahmed A; Seo, Sung-Yum

2017-06-01

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (-11.70, -12.1, -9.90 and -11.20kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds. Overall, bioactivity and ligand efficiency profiles suggested that the proposed hit may be more effective inhibitors for melanogenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ionization energies and electron affinities from a random-phase-approximation many-body Green's-function method including exchange interactions

NASA Astrophysics Data System (ADS)

Heßelmann, Andreas

2017-06-01

A many-body Green's-function method employing an infinite order summation of ring and exchange-ring contributions to the self-energy is presented. The individual correlation and relaxation contributions to the quasiparticle energies are calculated using an iterative scheme which utilizes density fitting of the particle-hole, particle-particle and hole-hole densities. It is shown that the ionization energies and electron affinities of this approach agree better with highly accurate coupled-cluster singles and doubles with perturbative triples energy difference results than those obtained with second-order Green's-function approaches. An analysis of the correlation and relaxation terms of the self-energy for the direct- and exchange-random-phase-approximation (RPA) Green's-function methods shows that the inclusion of exchange interactions leads to a reduction of the two contributions in magnitude. These differences, however, strongly cancel each other when summing the individual terms to the quasiparticle energies. Due to this, the direct- and exchange-RPA methods perform similarly for the description of ionization energies (IPs) and electron affinities (EAs). The coupled-cluster reference IPs and EAs, if corrected to the adiabatic energy differences between the neutral and charged molecules, were shown to be in very good agreement with experimental measurements.

Twin hydroxymethyluracil-A base pair steps define the binding site for the DNA-binding protein TF1.

PubMed

Grove, A; Figueiredo, M L; Galeone, A; Mayol, L; Geiduschek, E P

1997-05-16

The DNA-bending protein TF1 is the Bacillus subtilis bacteriophage SPO1-encoded homolog of the bacterial HU proteins and the Escherichia coli integration host factor. We recently proposed that TF1, which binds with high affinity (Kd was approximately 3 nM) to preferred sites within the hydroxymethyluracil (hmU)-containing phage genome, identifies its binding sites based on sequence-dependent DNA flexibility. Here, we show that two hmU-A base pair steps coinciding with two previously proposed sites of DNA distortion are critical for complex formation. The affinity of TF1 is reduced 10-fold when both of these hmU-A base pair steps are replaced with A-hmU, G-C, or C-G steps; only modest changes in affinity result when substitutions are made at other base pairs of the TF1 binding site. Replacement of all hmU residues with thymine decreases the affinity of TF1 greatly; remarkably, the high affinity is restored when the two hmU-A base pair steps corresponding to previously suggested sites of distortion are reintroduced into otherwise T-containing DNA. T-DNA constructs with 3-base bulges spaced apart by 9 base pairs of duplex also generate nM affinity of TF1. We suggest that twin hmU-A base pair steps located at the proposed sites of distortion are key to target site selection by TF1 and that recognition is based largely, if not entirely, on sequence-dependent DNA flexibility.

Design Method of Digital Optimal Control Scheme and Multiple Paralleled Bridge Type Current Amplifier for Generating Gradient Magnetic Fields in MRI Systems

NASA Astrophysics Data System (ADS)

Watanabe, Shuji; Takano, Hiroshi; Fukuda, Hiroya; Hiraki, Eiji; Nakaoka, Mutsuo

This paper deals with a digital control scheme of multiple paralleled high frequency switching current amplifier with four-quadrant chopper for generating gradient magnetic fields in MRI (Magnetic Resonance Imaging) systems. In order to track high precise current pattern in Gradient Coils (GC), the proposal current amplifier cancels the switching current ripples in GC with each other and designed optimum switching gate pulse patterns without influences of the large filter current ripple amplitude. The optimal control implementation and the linear control theory in GC current amplifiers have affinity to each other with excellent characteristics. The digital control system can be realized easily through the digital control implementation, DSPs or microprocessors. Multiple-parallel operational microprocessors realize two or higher paralleled GC current pattern tracking amplifier with optimal control design and excellent results are given for improving the image quality of MRI systems.

RAId_DbS: Peptide Identification using Database Searches with Realistic Statistics

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo

2007-01-01

Background The key to mass-spectrometry-based proteomics is peptide identification. A major challenge in peptide identification is to obtain realistic E-values when assigning statistical significance to candidate peptides. Results Using a simple scoring scheme, we propose a database search method with theoretically characterized statistics. Taking into account possible skewness in the random variable distribution and the effect of finite sampling, we provide a theoretical derivation for the tail of the score distribution. For every experimental spectrum examined, we collect the scores of peptides in the database, and find good agreement between the collected score statistics and our theoretical distribution. Using Student's t-tests, we quantify the degree of agreement between the theoretical distribution and the score statistics collected. The T-tests may be used to measure the reliability of reported statistics. When combined with reported P-value for a peptide hit using a score distribution model, this new measure prevents exaggerated statistics. Another feature of RAId_DbS is its capability of detecting multiple co-eluted peptides. The peptide identification performance and statistical accuracy of RAId_DbS are assessed and compared with several other search tools. The executables and data related to RAId_DbS are freely available upon request. PMID:17961253

A scoring scheme for evaluating magnetofossil identifications

NASA Astrophysics Data System (ADS)

Kopp, R. E.; Kirschvink, J. L.

2007-12-01

In many Quaternary lacustrine and marine settings, fossil magnetotactic bacteria are a major contributor to sedimentary magnetization [1]. Magnetite particles produced by magnetotactic bacteria have traits, shaped by natural selection, that increase the efficiency with which the bacteria utilize iron and also facilitate the recognition of the particles' biological origin. In particular, magnetotactic bacteria generally produce particles with characteristic shapes and narrow size and shape distributions that lie within the single domain stability field. The particles have effective positive magnetic anisotropy, produced by alignment in chains and frequently by particle elongation. In addition, the crystals are often nearly stochiometric and have few crystallographic defects. Yet, despite these distinctive traits, there are few identified magnetofossils that predate the Quaternary, and many putative identifications are highly controversial. We propose a six-criteria scoring scheme for evaluating identifications based on the quality of the geological, magnetic, and electron microscopic evidence. Our criteria are: (1) whether the geological context is well-constrained stratigraphically, and whether paleomagnetic evidence suggests a primary magnetization; (2) whether magnetic or microscopic evidence support the presence of significant single-domain magnetite; (3) whether magnetic or ferromagnetic resonance evidence indicates narrow size and shape distributions, and whether microscopic evidence reveals single-domain particles with truncated edges, elongate single-domain particles, and/or narrow size and shape distributions; (4) whether ferromagnetic resonance, low-temperature magnetic, or electron microscopic evidence reveals the presence of chains; (5) whether low-temperature magnetometry, energy dispersive X-ray spectroscopy, or other techniques demonstrate the near-stochiometry of the particles; and (6) whether high-resolution TEM indicates the near- absence of crystallographic defects. We use criterion 1 to set the threshold for determining whether a magnetofossil identification is robust. Criteria 3 and 4 are assigned numerical scores that range from 0 to 4, while criteria 2, 5, and 6 are evaluated based on presence or absence. Based on this scheme, the oldest robust magnetofossils yet found come from the Cretaceous chalk beds of southern England [2], though Lower Cambrian limestones of the Pestrotsvet Formation, Siberia Platform, only marginally fail to meet our robust criteria [3]. Although magnetofossils have also been reported from Proterozoic, Archean, and Martian rocks, none of these identifications are robust. References: [1] R. E. Kopp and J. L. Kirschvink (2007). Earth Sci. Rev. doi:10.1016/j.earscirev.2007.08.001. [2] P. Montgomery et al. (1998). Earth Planet. Sci. Lett. 156: 209-224. [3] S. B. R. Chang et al. (1987). Phys. Earth Planet. Int. 46: 289-303.

Identity, Affinity, Reality: Making the Case for Affinity Groups in Elementary School

ERIC Educational Resources Information Center

Parsons, Julie; Ridley, Kimberly

2012-01-01

Affinity groups are places where students build connections and process "ouch" moments from their classes. Children talk about the isolation they sometimes feel. The relationships students gain through race-based affinity groups enable them to feel less alone with their emotions and help them build a stronger sense of self. At the same…

LIBRA-WA: a web application for ligand binding site detection and protein function recognition.

PubMed

Toti, Daniele; Viet Hung, Le; Tortosa, Valentina; Brandi, Valentina; Polticelli, Fabio

2018-03-01

Recently, LIBRA, a tool for active/ligand binding site prediction, was described. LIBRA's effectiveness was comparable to similar state-of-the-art tools; however, its scoring scheme, output presentation, dependence on local resources and overall convenience were amenable to improvements. To solve these issues, LIBRA-WA, a web application based on an improved LIBRA engine, has been developed, featuring a novel scoring scheme consistently improving LIBRA's performance, and a refined algorithm that can identify binding sites hosted at the interface between different subunits. LIBRA-WA also sports additional functionalities like ligand clustering and a completely redesigned interface for an easier analysis of the output. Extensive tests on 373 apoprotein structures indicate that LIBRA-WA is able to identify the biologically relevant ligand/ligand binding site in 357 cases (∼96%), with the correct prediction ranking first in 349 cases (∼98% of the latter, ∼94% of the total). The earlier stand-alone tool has also been updated and dubbed LIBRA+, by integrating LIBRA-WA's improved engine for cross-compatibility purposes. LIBRA-WA and LIBRA+ are available at: http://www.computationalbiology.it/software.html. polticel@uniroma3.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

From Theory to Practice: Measuring end-of-life communication quality using multiple goals theory.

PubMed

Van Scoy, L J; Scott, A M; Reading, J M; Chuang, C H; Chinchilli, V M; Levi, B H; Green, M J

2017-05-01

To describe how multiple goals theory can be used as a reliable and valid measure (i.e., coding scheme) of the quality of conversations about end-of-life issues. We analyzed conversations from 17 conversations in which 68 participants (mean age=51years) played a game that prompted discussion in response to open-ended questions about end-of-life issues. Conversations (mean duration=91min) were audio-recorded and transcribed. Communication quality was assessed by three coders who assigned numeric scores rating how well individuals accomplished task, relational, and identity goals in the conversation. The coding measure, which results in a quantifiable outcome, yielded strong reliability (intra-class correlation range=0.73-0.89 and Cronbach's alpha range=0.69-0.89 for each of the coded domains) and validity (using multilevel nonlinear modeling, we detected significant variability in scores between games for each of the coded domains, all p-values <0.02). Our coding scheme provides a theory-based measure of end-of-life conversation quality that is superior to other methods of measuring communication quality. Our description of the coding method enables researches to adapt and apply this measure to communication interventions in other clinical contexts. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Host-Guest Complexes with Protein-Ligand-Like Affinities: Computational Analysis and Design

PubMed Central

Moghaddam, Sarvin; Inoue, Yoshihisa

2009-01-01

It has recently been discovered that guests combining a nonpolar core with cationic substituents bind cucurbit[7]uril (CB[7]) in water with ultra-high affinities. The present study uses the Mining Minima algorithm to study the physics of these extraordinary associations and to computationally test a new series of CB[7] ligands designed to bind with similarly high affinity. The calculations reproduce key experimental observations regarding the affinities of ferrocene-based guests with CB[7] and β-cyclodextrin and provide a coherent view of the roles of electrostatics and configurational entropy as determinants of affinity in these systems. The newly designed series of compounds is based on a bicyclo[2.2.2]octane core, which is similar in size and polarity to the ferrocene core of the existing series. Mining Minima predicts that these new compounds will, like the ferrocenes, bind CB[7] with extremely high affinities. PMID:19133781

Deconstructing Building Blocks: Preschoolers' Spatial Assembly Performance Relates to Early Mathematical Skills

ERIC Educational Resources Information Center

Verdine, Brian N.; Golinkoff, Roberta M.; Hirsh-Pasek, Kathryn; Newcombe, Nora S.; Filipowicz, Andrew T.; Chang, Alicia

2014-01-01

This study focuses on three main goals: First, 3-year-olds' spatial assembly skills are probed using interlocking block constructions (N = 102). A detailed scoring scheme provides insight into early spatial processing and offers information beyond a basic accuracy score. Second, the relation of spatial assembly to early mathematical skills…

Apply radiomics approach for early stage prognostic evaluation of ovarian cancer patients: a preliminary study

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Wang, Yunzhi; Thai, Theresa; Gunderson, Camille; Moxley, Katherine; Moore, Kathleen; Mannel, Robert; Liu, Hong; Zheng, Bin; Qiu, Yuchen

2017-03-01

Predicting metastatic tumor response to chemotherapy at early stage is critically important for improving efficacy of clinical trials of testing new chemotherapy drugs. However, using current response evaluation criteria in solid tumors (RECIST) guidelines only yields a limited accuracy to predict tumor response. In order to address this clinical challenge, we applied Radiomics approach to develop a new quantitative image analysis scheme, aiming to accurately assess the tumor response to new chemotherapy treatment, for the advanced ovarian cancer patients. During the experiment, a retrospective dataset containing 57 patients was assembled, each of which has two sets of CT images: pre-therapy and 4-6 week follow up CT images. A Radiomics based image analysis scheme was then applied on these images, which is composed of three steps. First, the tumors depicted on the CT images were segmented by a hybrid tumor segmentation scheme. Then, a total of 115 features were computed from the segmented tumors, which can be grouped as 1) volume based features; 2) density based features; and 3) wavelet features. Finally, an optimal feature cluster was selected based on the single feature performance and an equal-weighed fusion rule was applied to generate the final predicting score. The results demonstrated that the single feature achieved an area under the receiver operating characteristic curve (AUC) of 0.838+/-0.053. This investigation demonstrates that the Radiomic approach may have the potential in the development of high accuracy predicting model for early stage prognostic assessment of ovarian cancer patients.

Computing the binding affinity of Zn2+ in human carbonic anhydrase II on the basis of all-atom molecular dynamics simulations.

NASA Astrophysics Data System (ADS)

Wambo, Thierry; Rodriguez, Roberto

Human carbonic anhydrase II (hCAII) is a metalloenzyme with a Zinc cation at its binding site. The presence of the Zinc turns the protein into an efficient enzyme which catalyzes the reversible hydration of carbon dioxide into bicarbonate anion. Available X-ray structures of the apo-hCAII and holo-hCAII show no significant differences in the overall structure of these proteins. What difference, if any, is there between the structures of the hydrated apo-hCAII and holo? How can we use computer simulation to efficiently compute the binding affinity of Zinc to hCAII? We will present a scheme developed to compute the binding affinity of Zinc cation to hCAII on the basis of all-atom molecular dynamics simulation where Zinc is represented as a point charge and the CHARMM36 force field is used for running the dynamics of the system. Our computed binding affinity of the cation to hCAII is in good agreement with experiment, within the margin of error, while a look at the dynamics of the binding site suggests that in the absence of the Zinc, there is a re-organization of the nearby histidine residues which adopt a new distinct configuration. The authors are thankful for the NIH support through Grants GM084834 and GM060655. They also acknowledge the Texas Advanced Computing Center at the University of Texas at Austin for the supercomputing time. They thank Dr Liao Chen for his comments.

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study.

PubMed

Lv, Jun; Yang, Ming; Zhang, Jue; Wang, Xiaoying

2018-02-01

Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural network (CNN) to obtain motion-free abdominal images throughout the respiratory cycle. Abdominal data were acquired from 10 volunteers using a 1.5 T MRI system. The respiratory signal was extracted from the central-space spokes, and the acquired data were reordered in three bins according to the corresponding breathing signal. Retrospective image reconstruction of the three near-motion free respiratory phases was performed using non-Cartesian iterative SENSE reconstruction. Then, we trained a CNN to analyse the spatial transform among the different bins. This network could generate the displacement vector field and be applied to perform registration on unseen image pairs. To demonstrate the feasibility of this registration method, we compared the performance of three different registration approaches for accurate image fusion of three bins: non-motion corrected (NMC), local affine registration method (LREG) and CNN. Visualization of coronal images indicated that LREG had caused broken blood vessels, while the vessels of the CNN were sharper and more consecutive. As shown in the sagittal view, compared to NMC and CNN, distorted and blurred liver contours were caused by LREG. At the same time, zoom-in axial images presented that the vessels were delineated more clearly by CNN than LREG. The statistical results of the signal-to-noise ratio, visual score, vessel sharpness and registration time over all volunteers were compared among the NMC, LREG and CNN approaches. The SNR indicated that the CNN acquired the best image quality (207.42 ± 96.73), which was better than NMC (116.67 ± 44.70) and LREG (187.93 ± 96.68). The image visual score agreed with SNR, marking CNN (3.85 ± 0.12) as the best, followed by LREG (3.43 ± 0.13) and NMC (2.55 ± 0.09). A vessel sharpness assessment yielded similar values between the CNN (0.81 ± 0.03) and LREG (0.80 ± 0.04), differentiating them from the NMC (0.78 ± 0.06). When compared with the LREG-based reconstruction, the CNN-based reconstruction reduces the registration time from 1 h to 1 min. Our preliminary results demonstrate the feasibility of the CNN-based approach, and this scheme outperforms the NMC- and LREG-based methods. Advances in knowledge: This method reduces the registration time from ~1 h to ~1 min, which has promising prospects for clinical use. To the best of our knowledge, this study shows the first convolutional neural network-based registration method to be applied in abdominal images.

Improving lung cancer prognosis assessment by incorporating synthetic minority oversampling technique and score fusion method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Shiju; Qian, Wei; Guan, Yubao

2016-06-15

Purpose: This study aims to investigate the potential to improve lung cancer recurrence risk prediction performance for stage I NSCLS patients by integrating oversampling, feature selection, and score fusion techniques and develop an optimal prediction model. Methods: A dataset involving 94 early stage lung cancer patients was retrospectively assembled, which includes CT images, nine clinical and biological (CB) markers, and outcome of 3-yr disease-free survival (DFS) after surgery. Among the 94 patients, 74 remained DFS and 20 had cancer recurrence. Applying a computer-aided detection scheme, tumors were segmented from the CT images and 35 quantitative image (QI) features were initiallymore » computed. Two normalized Gaussian radial basis function network (RBFN) based classifiers were built based on QI features and CB markers separately. To improve prediction performance, the authors applied a synthetic minority oversampling technique (SMOTE) and a BestFirst based feature selection method to optimize the classifiers and also tested fusion methods to combine QI and CB based prediction results. Results: Using a leave-one-case-out cross-validation (K-fold cross-validation) method, the computed areas under a receiver operating characteristic curve (AUCs) were 0.716 ± 0.071 and 0.642 ± 0.061, when using the QI and CB based classifiers, respectively. By fusion of the scores generated by the two classifiers, AUC significantly increased to 0.859 ± 0.052 (p < 0.05) with an overall prediction accuracy of 89.4%. Conclusions: This study demonstrated the feasibility of improving prediction performance by integrating SMOTE, feature selection, and score fusion techniques. Combining QI features and CB markers and performing SMOTE prior to feature selection in classifier training enabled RBFN based classifier to yield improved prediction accuracy.« less

Magnetic Viruses: Utilizing Self-Assembly for Biomedical Applications

NASA Astrophysics Data System (ADS)

Hoffmann, Axel

2006-03-01

Magnetic nanoparticles coated with biochemical surfactants have emerged recently as an important component for enabling many biological and medical applications. We implemented a biotemplating approach to create such magnetic nanoparticles by utilizing native protein capsid shells derived in high yield from the T7 bacteriophage virus. The magnetic nanoparticles are grown via bio-mineralization reactions inside of hollowed-out capsids that retain their original chemical recognition properties. The resultant ``magnetic viruses'' are uniform in geometry, physical properties, and biochemical functionality. This makes these viruses ideally suited for many biomedical applications among which we investigated specifically a novel sensing scheme for target recognition based on Brownian relaxation. For this scheme we use the ac-susceptibility of the functionalized magnetic nanoparticles suspended in liquid. Upon binding the target of interest to the particles, their Brownian relaxation time is modified, which is readily detected by a change of the frequency dependence of the magnetic susceptibility. This scheme has several advantages; (i) it requires only one binding event for sensing; (ii) there is a useful signal both in the absence and presence of the target; (iii) the signal contains information about the size of the target besides the biochemical affinity; and (iv) since the binding modifies the magnetic susceptibility of the magnetic particles there is no need for removing unbound labels. C. Liu, S.-H. Chung, Q. Jin, A. Sutton, F. Yan, B. K. Kay, S. D. Bader, L. Makowski, and L. Chen, J. Magn. Magn. Mater, in press. S.H. Chung, A. Hoffmann, S. D. Bader, C. Liu, B. Kay, L. Makowski, and L. Chen, Appl. Phys. Lett. 85, 2971 (2004) ; S. H. Chung, A. Hoffmann, K. Guslienko, S. D. Bader, C. Liu, B. Kay, L. Makowski, and L. Chen, J. Appl. Phys. 97, 10R101 (2005).

Radar-derived Quantitative Precipitation Estimation in Complex Terrain over the Eastern Tibetan Plateau

NASA Astrophysics Data System (ADS)

Gou, Y.

2017-12-01

Quantitative Precipitation Estimation (QPE) is one of the important applications of weather radars. However, in complex terrain such as Tibetan Plateau, it is a challenging task to obtain an optimal Z-R relation due to the complex space time variability in precipitation microphysics. This paper develops two radar QPE schemes respectively based on Reflectivity Threshold (RT) and Storm Cell Identification and Tracking (SCIT) algorithms using observations from 11 Doppler weather radars and 3294 rain gauges over the Eastern Tibetan Plateau (ETP). These two QPE methodologies are evaluated extensively using four precipitation events that are characterized by different meteorological features. Precipitation characteristics of independent storm cells associated with these four events, as well as the storm-scale differences, are investigated using short-term vertical profiles of reflectivity clusters. Evaluation results show that the SCIT-based rainfall approach performs better than the simple RT-based method in all precipitation events in terms of score comparison using validation gauge measurements as references, with higher correlation (than 75.74%), lower mean absolute error (than 82.38%) and root-mean-square error (than 89.04%) of all the comparative frames. It is also found that the SCIT-based approach can effectively mitigate the radar QPE local error and represent precipitation spatiotemporal variability better than RT-based scheme.

The feasibility of an efficient drug design method with high-performance computers.

PubMed

Yamashita, Takefumi; Ueda, Akihiko; Mitsui, Takashi; Tomonaga, Atsushi; Matsumoto, Shunji; Kodama, Tatsuhiko; Fujitani, Hideaki

2015-01-01

In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based binding free energy prediction has a huge computational cost, it is feasible with the latest 10 petaflop-scale computer. The supercomputer-assisted drug design approach also involves two important feedback procedures: The first feedback is generated from the MD-based binding free energy prediction step to the drug design step. While the experimental feedback usually provides binding affinities of tens of compounds at one time, the supercomputer allows us to simultaneously obtain the binding free energies of hundreds of compounds. Because the number of calculated binding free energies is sufficiently large, the compounds can be classified into different categories whose properties will aid in the design of the next generation of drug candidates. The second feedback, which occurs from the experiments to the MD simulations, is important to validate the simulation parameters. To demonstrate this, we compare the binding free energies calculated with various force fields to the experimental ones. The results indicate that the prediction will not be very successful, if we use an inaccurate force field. By improving/validating such simulation parameters, the next prediction can be made more accurate.

An improved method to detect correct protein folds using partial clustering.

PubMed

Zhou, Jianjun; Wishart, David S

2013-01-16

Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient "partial" clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either C(α) RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance.

An improved method to detect correct protein folds using partial clustering

PubMed Central

2013-01-01

Background Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient “partial“ clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. Results We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either Cα RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. Conclusions The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance. PMID:23323835

Ballistic Resistance of Armored Passenger Vehicles: Test Protocols and Quality Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeffrey M. Lacy; Robert E. Polk

2005-07-01

This guide establishes a test methodology for determining the overall ballistic resistance of the passenger compartment of assembled nontactical armored passenger vehicles (APVs). Because ballistic testing of every piece of every component of an armored vehicle is impractical, if not impossible, this guide describes a testing scheme based on statistical sampling of exposed component surface areas. Results from the test of the sampled points are combined to form a test score that reflects the probability of ballistic penetration into the passenger compartment of the vehicle.

Mathematical model of the loan portfolio dynamics in the form of Markov chain considering the process of new customers attraction

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana

2017-12-01

Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.

Evaluation of Several Two-Step Scoring Functions Based on Linear Interaction Energy, Effective Ligand Size, and Empirical Pair Potentials for Prediction of Protein-Ligand Binding Geometry and Free Energy

PubMed Central

Rahaman, Obaidur; Estrada, Trilce P.; Doren, Douglas J.; Taufer, Michela; Brooks, Charles L.; Armen, Roger S.

2011-01-01

The performance of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for “step 2 discrimination” were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only “interacting” ligand atoms as the “effective size” of the ligand, and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and five-fold cross validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new dataset (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ dataset where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts. PMID:21644546

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

PubMed

Rahaman, Obaidur; Estrada, Trilce P; Doren, Douglas J; Taufer, Michela; Brooks, Charles L; Armen, Roger S

2011-09-26

The performances of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for "step 2 discrimination" were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only "interacting" ligand atoms as the "effective size" of the ligand and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and 5-fold cross-validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new data set (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ data set where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts.

Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

2015-06-12

Docking scoring functions can be used to predict the strength of protein-ligand binding. It is widely believed that training a scoring function with low-quality data is detrimental for its predictive performance. Nevertheless, there is a surprising lack of systematic validation experiments in support of this hypothesis. In this study, we investigated to which extent training a scoring function with data containing low-quality structural and binding data is detrimental for predictive performance. We actually found that low-quality data is not only non-detrimental, but beneficial for the predictive performance of machine-learning scoring functions, though the improvement is less important than that coming from high-quality data. Furthermore, we observed that classical scoring functions are not able to effectively exploit data beyond an early threshold, regardless of its quality. This demonstrates that exploiting a larger data volume is more important for the performance of machine-learning scoring functions than restricting to a smaller set of higher data quality.

Accurate registration of temporal CT images for pulmonary nodules detection

NASA Astrophysics Data System (ADS)

Yan, Jichao; Jiang, Luan; Li, Qiang

2017-02-01

Interpretation of temporal CT images could help the radiologists to detect some subtle interval changes in the sequential examinations. The purpose of this study was to develop a fully automated scheme for accurate registration of temporal CT images for pulmonary nodule detection. Our method consisted of three major registration steps. Firstly, affine transformation was applied in the segmented lung region to obtain global coarse registration images. Secondly, B-splines based free-form deformation (FFD) was used to refine the coarse registration images. Thirdly, Demons algorithm was performed to align the feature points extracted from the registered images in the second step and the reference images. Our database consisted of 91 temporal CT cases obtained from Beijing 301 Hospital and Shanghai Changzheng Hospital. The preliminary results showed that approximately 96.7% cases could obtain accurate registration based on subjective observation. The subtraction images of the reference images and the rigid and non-rigid registered images could effectively remove the normal structures (i.e. blood vessels) and retain the abnormalities (i.e. pulmonary nodules). This would be useful for the screening of lung cancer in our future study.

Structure-Based Rational Design of a Toll-like Receptor 4 (TLR4) Decoy Receptor with High Binding Affinity for a Target Protein

PubMed Central

Lee, Sang-Chul; Hong, Seungpyo; Park, Keunwan; Jeon, Young Ho; Kim, Dongsup; Cheong, Hae-Kap; Kim, Hak-Sung

2012-01-01

Repeat proteins are increasingly attracting much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural features. Nonetheless, engineering interaction interface and understanding molecular basis for affinity maturation of repeat proteins still remain a challenge. Here, we present a structure-based rational design of a repeat protein with high binding affinity for a target protein. As a model repeat protein, a Toll-like receptor4 (TLR4) decoy receptor composed of leucine-rich repeat (LRR) modules was used, and its interaction interface was rationally engineered to increase the binding affinity for myeloid differentiation protein 2 (MD2). Based on the complex crystal structure of the decoy receptor with MD2, we first designed single amino acid substitutions in the decoy receptor, and obtained three variants showing a binding affinity (KD) one-order of magnitude higher than the wild-type decoy receptor. The interacting modes and contributions of individual residues were elucidated by analyzing the crystal structures of the single variants. To further increase the binding affinity, single positive mutations were combined, and two double mutants were shown to have about 3000- and 565-fold higher binding affinities than the wild-type decoy receptor. Molecular dynamics simulations and energetic analysis indicate that an additive effect by two mutations occurring at nearby modules was the major contributor to the remarkable increase in the binding affinities. PMID:22363519

Robust feature matching via support-line voting and affine-invariant ratios

NASA Astrophysics Data System (ADS)

Li, Jiayuan; Hu, Qingwu; Ai, Mingyao; Zhong, Ruofei

2017-10-01

Robust image matching is crucial for many applications of remote sensing and photogrammetry, such as image fusion, image registration, and change detection. In this paper, we propose a robust feature matching method based on support-line voting and affine-invariant ratios. We first use popular feature matching algorithms, such as SIFT, to obtain a set of initial matches. A support-line descriptor based on multiple adaptive binning gradient histograms is subsequently applied in the support-line voting stage to filter outliers. In addition, we use affine-invariant ratios computed by a two-line structure to refine the matching results and estimate the local affine transformation. The local affine model is more robust to distortions caused by elevation differences than the global affine transformation, especially for high-resolution remote sensing images and UAV images. Thus, the proposed method is suitable for both rigid and non-rigid image matching problems. Finally, we extract as many high-precision correspondences as possible based on the local affine extension and build a grid-wise affine model for remote sensing image registration. We compare the proposed method with six state-of-the-art algorithms on several data sets and show that our method significantly outperforms the other methods. The proposed method achieves 94.46% average precision on 15 challenging remote sensing image pairs, while the second-best method, RANSAC, only achieves 70.3%. In addition, the number of detected correct matches of the proposed method is approximately four times the number of initial SIFT matches.

Blind Compressed Sensing Enables 3-Dimensional Dynamic Free Breathing Magnetic Resonance Imaging of Lung Volumes and Diaphragm Motion.

PubMed

Bhave, Sampada; Lingala, Sajan Goud; Newell, John D; Nagle, Scott K; Jacob, Mathews

2016-06-01

The objective of this study was to increase the spatial and temporal resolution of dynamic 3-dimensional (3D) magnetic resonance imaging (MRI) of lung volumes and diaphragm motion. To achieve this goal, we evaluate the utility of the proposed blind compressed sensing (BCS) algorithm to recover data from highly undersampled measurements. We evaluated the performance of the BCS scheme to recover dynamic data sets from retrospectively and prospectively undersampled measurements. We also compared its performance against that of view-sharing, the nuclear norm minimization scheme, and the l1 Fourier sparsity regularization scheme. Quantitative experiments were performed on a healthy subject using a fully sampled 2D data set with uniform radial sampling, which was retrospectively undersampled with 16 radial spokes per frame to correspond to an undersampling factor of 8. The images obtained from the 4 reconstruction schemes were compared with the fully sampled data using mean square error and normalized high-frequency error metrics. The schemes were also compared using prospective 3D data acquired on a Siemens 3 T TIM TRIO MRI scanner on 8 healthy subjects during free breathing. Two expert cardiothoracic radiologists (R1 and R2) qualitatively evaluated the reconstructed 3D data sets using a 5-point scale (0-4) on the basis of spatial resolution, temporal resolution, and presence of aliasing artifacts. The BCS scheme gives better reconstructions (mean square error = 0.0232 and normalized high frequency = 0.133) than the other schemes in the 2D retrospective undersampling experiments, producing minimally distorted reconstructions up to an acceleration factor of 8 (16 radial spokes per frame). The prospective 3D experiments show that the BCS scheme provides visually improved reconstructions than the other schemes do. The BCS scheme provides improved qualitative scores over nuclear norm and l1 Fourier sparsity regularization schemes in the temporal blurring and spatial blurring categories. The qualitative scores for aliasing artifacts in the images reconstructed by nuclear norm scheme and BCS scheme are comparable.The comparisons of the tidal volume changes also show that the BCS scheme has less temporal blurring as compared with the nuclear norm minimization scheme and the l1 Fourier sparsity regularization scheme. The minute ventilation estimated by BCS for tidal breathing in supine position (4 L/min) and the measured supine inspiratory capacity (1.5 L) is in good correlation with the literature. The improved performance of BCS can be explained by its ability to efficiently adapt to the data, thus providing a richer representation of the signal. The feasibility of the BCS scheme was demonstrated for dynamic 3D free breathing MRI of lung volumes and diaphragm motion. A temporal resolution of ∼500 milliseconds, spatial resolution of 2.7 × 2.7 × 10 mm, with whole lung coverage (16 slices) was achieved using the BCS scheme.

Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier

NASA Astrophysics Data System (ADS)

Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

2018-03-01

The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task.

Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier.

PubMed

Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

2018-03-01

The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin

2018-05-01

This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC  =  0.65  ±  0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p  <  0.01). Thus, this study demonstrated that CAD-generated false-positives might include valuable information, which needs to be further explored for identifying and/or developing more effective imaging markers for predicting short-term breast cancer risk.

Toward an optimisation technique for dynamically monitored environment

NASA Astrophysics Data System (ADS)

Shurrab, Orabi M.

2016-10-01

The data fusion community has introduced multiple procedures of situational assessments; this is to facilitate timely responses to emerging situations. More directly, the process refinement of the Joint Directors of Laboratories (JDL) is a meta-process to assess and improve the data fusion task during real-time operation. In other wording, it is an optimisation technique to verify the overall data fusion performance, and enhance it toward the top goals of the decision-making resources. This paper discusses the theoretical concept of prioritisation. Where the analysts team is required to keep an up to date with the dynamically changing environment, concerning different domains such as air, sea, land, space and cyberspace. Furthermore, it demonstrates an illustration example of how various tracking activities are ranked, simultaneously into a predetermined order. Specifically, it presents a modelling scheme for a case study based scenario, where the real-time system is reporting different classes of prioritised events. Followed by a performance metrics for evaluating the prioritisation process of situational awareness (SWA) domain. The proposed performance metrics has been designed and evaluated using an analytical approach. The modelling scheme represents the situational awareness system outputs mathematically, in the form of a list of activities. Such methods allowed the evaluation process to conduct a rigorous analysis of the prioritisation process, despite any constrained related to a domain-specific configuration. After conducted three levels of assessments over three separates scenario, The Prioritisation Capability Score (PCS) has provided an appropriate scoring scheme for different ranking instances, Indeed, from the data fusion perspectives, the proposed metric has assessed real-time system performance adequately, and it is capable of conducting a verification process, to direct the operator's attention to any issue, concerning the prioritisation capability of situational awareness domain.

Mathematical analysis of frontal affinity chromatography in particle and membrane configurations.

PubMed

Tejeda-Mansir, A; Montesinos, R M; Guzmán, R

2001-10-30

The scaleup and optimization of large-scale affinity-chromatographic operations in the recovery, separation and purification of biochemical components is of major industrial importance. The development of mathematical models to describe affinity-chromatographic processes, and the use of these models in computer programs to predict column performance is an engineering approach that can help to attain these bioprocess engineering tasks successfully. Most affinity-chromatographic separations are operated in the frontal mode, using fixed-bed columns. Purely diffusive and perfusion particles and membrane-based affinity chromatography are among the main commercially available technologies for these separations. For a particular application, a basic understanding of the main similarities and differences between particle and membrane frontal affinity chromatography and how these characteristics are reflected in the transport models is of fundamental relevance. This review presents the basic theoretical considerations used in the development of particle and membrane affinity chromatography models that can be applied in the design and operation of large-scale affinity separations in fixed-bed columns. A transport model for column affinity chromatography that considers column dispersion, particle internal convection, external film resistance, finite kinetic rate, plus macropore and micropore resistances is analyzed as a framework for exploring further the mathematical analysis. Such models provide a general realistic description of almost all practical systems. Specific mathematical models that take into account geometric considerations and transport effects have been developed for both particle and membrane affinity chromatography systems. Some of the most common simplified models, based on linear driving-force (LDF) and equilibrium assumptions, are emphasized. Analytical solutions of the corresponding simplified dimensionless affinity models are presented. Particular methods for estimating the parameters that characterize the mass-transfer and adsorption mechanisms in affinity systems are described.

A global/local affinity graph for image segmentation.

PubMed

Xiaofang Wang; Yuxing Tang; Masnou, Simon; Liming Chen

2015-04-01

Construction of a reliable graph capturing perceptual grouping cues of an image is fundamental for graph-cut based image segmentation methods. In this paper, we propose a novel sparse global/local affinity graph over superpixels of an input image to capture both short- and long-range grouping cues, and thereby enabling perceptual grouping laws, including proximity, similarity, continuity, and to enter in action through a suitable graph-cut algorithm. Moreover, we also evaluate three major visual features, namely, color, texture, and shape, for their effectiveness in perceptual segmentation and propose a simple graph fusion scheme to implement some recent findings from psychophysics, which suggest combining these visual features with different emphases for perceptual grouping. In particular, an input image is first oversegmented into superpixels at different scales. We postulate a gravitation law based on empirical observations and divide superpixels adaptively into small-, medium-, and large-sized sets. Global grouping is achieved using medium-sized superpixels through a sparse representation of superpixels' features by solving a ℓ0-minimization problem, and thereby enabling continuity or propagation of local smoothness over long-range connections. Small- and large-sized superpixels are then used to achieve local smoothness through an adjacent graph in a given feature space, and thus implementing perceptual laws, for example, similarity and proximity. Finally, a bipartite graph is also introduced to enable propagation of grouping cues between superpixels of different scales. Extensive experiments are carried out on the Berkeley segmentation database in comparison with several state-of-the-art graph constructions. The results show the effectiveness of the proposed approach, which outperforms state-of-the-art graphs using four different objective criteria, namely, the probabilistic rand index, the variation of information, the global consistency error, and the boundary displacement error.

Comparison of different assimilation schemes in an operational assimilation system with Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Yan, Yajing; Barth, Alexander; Beckers, Jean-Marie; Candille, Guillem; Brankart, Jean-Michel; Brasseur, Pierre

2016-04-01

In this paper, four assimilation schemes, including an intermittent assimilation scheme (INT) and three incremental assimilation schemes (IAU 0, IAU 50 and IAU 100), are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The three IAU schemes differ from each other in the position of the increment update window that has the same size as the assimilation window. 0, 50 and 100 correspond to the degree of superposition of the increment update window on the current assimilation window. Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/observation difference, as well as by rank histogram before the assimilation experiments The relevance of each assimilation scheme is evaluated through analyses on thermohaline variables and the current velocities. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semi-independent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system.

Atlas-based segmentation of brainstem regions in neuromelanin-sensitive magnetic resonance images

NASA Astrophysics Data System (ADS)

Puigvert, Marc; Castellanos, Gabriel; Uranga, Javier; Abad, Ricardo; Fernández-Seara, María. A.; Pastor, Pau; Pastor, María. A.; Muñoz-Barrutia, Arrate; Ortiz de Solórzano, Carlos

2015-03-01

We present a method for the automatic delineation of two neuromelanin rich brainstem structures -substantia nigra pars compacta (SN) and locus coeruleus (LC)- in neuromelanin sensitive magnetic resonance images of the brain. The segmentation method uses a dynamic multi-image reference atlas and a pre-registration atlas selection strategy. To create the atlas, a pool of 35 images of healthy subjects was pair-wise pre-registered and clustered in groups using an affinity propagation approach. Each group of the atlas is represented by a single exemplar image. Each new target image to be segmented is registered to the exemplars of each cluster. Then all the images of the highest performing clusters are enrolled into the final atlas, and the results of the registration with the target image are propagated using a majority voting approach. All registration processes used combined one two-stage affine and one elastic B-spline algorithm, to account for global positioning, region selection and local anatomic differences. In this paper, we present the algorithm, with emphasis in the atlas selection method and the registration scheme. We evaluate the performance of the atlas selection strategy using 35 healthy subjects and 5 Parkinson's disease patients. Then, we quantified the volume and contrast ratio of neuromelanin signal of these structures in 47 normal subjects and 40 Parkinson's disease patients to confirm that this method can detect neuromelanin-containing neurons loss in Parkinson's disease patients and could eventually be used for the early detection of SN and LC damage.

Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors.

PubMed

Atanasova, Mariyana; Yordanov, Nikola; Dimitrov, Ivan; Berkov, Strahil; Doytchinova, Irini

2015-06-01

A training set of 22 synthetic galantamine derivatives binding to acetylcholinesterase was docked by GOLD and the protocol was optimized in terms of scoring function, rigidity/flexibility of the binding site, presence/absence of a water molecule inside and radius of the binding site. A moderate correlation was found between the affinities of compounds expressed as pIC50 values and their docking scores. The optimized docking protocol was validated by an external test set of 11 natural galantamine derivatives and the correlation coefficient between the docking scores and the pIC50 values was 0.800. The derived relationship was used to analyze the interactions between galantamine derivatives and AChE. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Non-affine deformations in polymer hydrogels

PubMed Central

Wen, Qi; Basu, Anindita; Janmey, Paul A.; Yodh, A. G.

2012-01-01

Most theories of soft matter elasticity assume that the local strain in a sample after deformation is identical everywhere and equal to the macroscopic strain, or equivalently that the deformation is affine. We discuss the elasticity of hydrogels of crosslinked polymers with special attention to affine and non-affine theories of elasticity. Experimental procedures to measure non-affine deformations are also described. Entropic theories, which account for gel elasticity based on stretching out individual polymer chains, predict affine deformations. In contrast, simulations of network deformation that result in bending of the stiff constituent filaments generally predict non-affine behavior. Results from experiments show significant non-affine deformation in hydrogels even when they are formed by flexible polymers for which bending would appear to be negligible compared to stretching. However, this finding is not necessarily an experimental proof of the non-affine model for elasticity. We emphasize the insights gained from experiments using confocal rheoscope and show that, in addition to filament bending, sample micro-inhomogeneity can be a significant alternative source of non-affine deformation. PMID:23002395

Toward the Automated Scoring of Written Arguments: Developing an Innovative Approach for Annotation. Research Report. ETS RR-17-11

ERIC Educational Resources Information Center

Song, Yi; Deane, Paul; Beigman Klebanov, Beata

2017-01-01

This project focuses on laying the foundations for automated analysis of argumentation schemes, supporting identification and classification of the arguments being made in a text, for the purpose of scoring the quality of written analyses of arguments. We developed annotation protocols for 20 argument prompts from a college-level test under the…

Assessing the Incremental Value of KABC-II Luria Model Scores in Predicting Achievement: What Do They Tell Us beyond the MPI?

ERIC Educational Resources Information Center

McGill, Ryan J.; Spurgin, Angelia R.

2016-01-01

The current study examined the incremental validity of the Luria interpretive scheme for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) for predicting scores on the Kaufman Test of Educational Achievement-Second Edition (KTEA-II). All participants were children and adolescents (N = 2,025) drawn from the nationally…

Impact of integrated child development scheme on child malnutrition in West Bengal, India.

PubMed

Dutta, Arijita; Ghosh, Smritikana

2017-10-01

With child malnutrition detected as a persistent problem in most of the developing countries, public policy has been directed towards offering community-based supplementary feeding provision and nutritional information to caregivers. India, being no exception, has initiated these programs as early as 1970s under integrated child development scheme. Using propensity score matching technique on primary data of 390 households in two districts of West Bengal, an Eastern state in India, the study finds that impact of being included in the program and receiving supplementary feeding is insignificant on child stunting measures, though the program can break the intractable barriers of child stunting only when the child successfully receives not only just the supplementary feeding but also his caregiver collects crucial information on nutritional awareness and growth trajectory of the child. Availability of regular eggs in the feeding diet too can reduce protein-related undernutrition. Focusing on just feeding means low depth of other services offered under integrated child development scheme, including pre-school education, nutritional awareness, and hygiene behavior; thus repealing a part of the apparent food-secure population who puts far more importance on the latter services. © 2016 John Wiley & Sons Ltd.

A new scoring method for evaluating the performance of earthquake forecasts and predictions

NASA Astrophysics Data System (ADS)

Zhuang, J.

2009-12-01

This study presents a new method, namely the gambling score, for scoring the performance of earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. A fair scoring scheme should reward the success in a way that is compatible with the risk taken. Suppose that we have the reference model, usually the Poisson model for usual cases or Omori-Utsu formula for the case of forecasting aftershocks, which gives probability p0 that at least 1 event occurs in a given space-time-magnitude window. The forecaster, similar to a gambler, who starts with a certain number of reputation points, bets 1 reputation point on ``Yes'' or ``No'' according to his forecast, or bets nothing if he performs a NA-prediction. If the forecaster bets 1 reputation point of his reputations on ``Yes" and loses, the number of his reputation points is reduced by 1; if his forecasts is successful, he should be rewarded (1-p0)/p0 reputation points. The quantity (1-p0)/p0 is the return (reward/bet) ratio for bets on ``Yes''. In this way, if the reference model is correct, the expected return that he gains from this bet is 0. This rule also applies to probability forecasts. Suppose that p is the occurrence probability of an earthquake given by the forecaster. We can regard the forecaster as splitting 1 reputation point by betting p on ``Yes'' and 1-p on ``No''. In this way, the forecaster's expected pay-off based on the reference model is still 0. From the viewpoints of both the reference model and the forecaster, the rule for rewarding and punishment is fair. This method is also extended to the continuous case of point process models, where the reputation points bet by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

PRINCIPLES OF AFFINITY-BASED BIOSENSORS

EPA Science Inventory

Despite the amount of resources that have been invested by national and international academic, government, and commercial sectors to develop affinity-based biosensor products, little obvious success has been realized through commercialization of these devices for specific applic...

Shape based segmentation of MRIs of the bones in the knee using phase and intensity information

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Bourgeat, Pierrick; Crozier, Stuart; Ourselin, Sébastien

2007-03-01

The segmentation of the bones from MR images is useful for performing subsequent segmentation and quantitative measurements of cartilage tissue. In this paper, we present a shape based segmentation scheme for the bones that uses texture features derived from the phase and intensity information in the complex MR image. The phase can provide additional information about the tissue interfaces, but due to the phase unwrapping problem, this information is usually discarded. By using a Gabor filter bank on the complex MR image, texture features (including phase) can be extracted without requiring phase unwrapping. These texture features are then analyzed using a support vector machine classifier to obtain probability tissue matches. The segmentation of the bone is fully automatic and performed using a 3D active shape model based approach driven using gradient and texture information. The 3D active shape model is automatically initialized using a robust affine registration. The approach is validated using a database of 18 FLASH MR images that are manually segmented, with an average segmentation overlap (Dice similarity coefficient) of 0.92 compared to 0.9 obtained using the classifier only.

PharmDock: a pharmacophore-based docking program

PubMed Central

2014-01-01

Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock. PMID:24739488

Ebolavirus Nucleoprotein C-Termini Potently Attract Single Domain Antibodies Enabling Monoclonal Affinity Reagent Sandwich Assay (MARSA) Formulation

PubMed Central

Sherwood, Laura J.; Hayhurst, Andrew

2013-01-01

Background Antigen detection assays can play an important part in environmental surveillance and diagnostics for emerging threats. We are interested in accelerating assay formulation; targeting the agents themselves to bypass requirements for a priori genome information or surrogates. Previously, using in vitro affinity reagent selection on Marburg virus we rapidly established monoclonal affinity reagent sandwich assay (MARSA) where one recombinant antibody clone was both captor and tracer for polyvalent nucleoprotein (NP). Hypothesizing that the closely related Ebolavirus genus may share the same Achilles' heel, we redirected the scheme to see whether similar assays could be delivered and began to explore their mechanism. Methods and Findings In parallel we selected panels of llama single domain antibodies (sdAb) from a semi-synthetic library against Zaire, Sudan, Ivory Coast, and Reston Ebola viruses. Each could perform as both captor and tracer in the same antigen sandwich capture assay thereby forming MARSAs. All sdAb were specific for NP and those tested required the C-terminal domain for recognition. Several clones were cross-reactive, indicating epitope conservation across the Ebolavirus genus. Analysis of two immune shark sdAb revealed they also targeted the C-terminal domain, and could be similarly employed, yet were less sensitive than a comparable llama sdAb despite stemming from immune selections. Conclusions The C-terminal domain of Ebolavirus NP is a strong attractant for antibodies and enables sensitive sandwich immunoassays to be rapidly generated using a single antibody clone. The polyvalent nature of nucleocapsid borne NP and display of the C-terminal region likely serves as a bountiful affinity sink during selections, and a highly avid target for subsequent immunoassay capture. Combined with the high degree of amino acid conservation through 37 years and across wide geographies, this domain makes an ideal handle for monoclonal affinity reagent driven antigen sandwich assays for the Ebolavirus genus. PMID:23577211

PROCOS: computational analysis of protein-protein complexes.

PubMed

Fink, Florian; Hochrein, Jochen; Wolowski, Vincent; Merkl, Rainer; Gronwald, Wolfram

2011-09-01

One of the main challenges in protein-protein docking is a meaningful evaluation of the many putative solutions. Here we present a program (PROCOS) that calculates a probability-like measure to be native for a given complex. In contrast to scores often used for analyzing complex structures, the calculated probabilities offer the advantage of providing a fixed range of expected values. This will allow, in principle, the comparison of models corresponding to different targets that were solved with the same algorithm. Judgments are based on distributions of properties derived from a large database of native and false complexes. For complex analysis PROCOS uses these property distributions of native and false complexes together with a support vector machine (SVM). PROCOS was compared to the established scoring schemes of ZRANK and DFIRE. Employing a set of experimentally solved native complexes, high probability values above 50% were obtained for 90% of these structures. Next, the performance of PROCOS was tested on the 40 binary targets of the Dockground decoy set, on 14 targets of the RosettaDock decoy set and on 9 targets that participated in the CAPRI scoring evaluation. Again the advantage of using a probability-based scoring system becomes apparent and a reasonable number of near native complexes was found within the top ranked complexes. In conclusion, a novel fully automated method is presented that allows the reliable evaluation of protein-protein complexes. Copyright © 2011 Wiley Periodicals, Inc.

Development and Testing of Enhanced Affinity Reagents for Use in Environmental Detection Assays

DTIC Science & Technology

Current affinity reagent development methodologies generally rely on costly and slow antibody production that is based on animal inoculations with...attenuated, inactivated, or surrogate biothreat agents. Recent literature has demonstrated that the de novo computer design of recombinant affinity

Fisher's method of scoring in statistical image reconstruction: comparison of Jacobi and Gauss-Seidel iterative schemes.

PubMed

Hudson, H M; Ma, J; Green, P

1994-01-01

Many algorithms for medical image reconstruction adopt versions of the expectation-maximization (EM) algorithm. In this approach, parameter estimates are obtained which maximize a complete data likelihood or penalized likelihood, in each iteration. Implicitly (and sometimes explicitly) penalized algorithms require smoothing of the current reconstruction in the image domain as part of their iteration scheme. In this paper, we discuss alternatives to EM which adapt Fisher's method of scoring (FS) and other methods for direct maximization of the incomplete data likelihood. Jacobi and Gauss-Seidel methods for non-linear optimization provide efficient algorithms applying FS in tomography. One approach uses smoothed projection data in its iterations. We investigate the convergence of Jacobi and Gauss-Seidel algorithms with clinical tomographic projection data.

Alkali Metal Cation versus Proton and Methyl Cation Affinities: Structure and Bonding Mechanism

PubMed Central

Boughlala, Zakaria; Fonseca Guerra, Célia

2016-01-01

Abstract We have analyzed the structure and bonding of gas‐phase Cl−X and [HCl−X]+ complexes for X+= H+, CH3 +, Li+, and Na+, using relativistic density functional theory (DFT). We wish to establish a quantitative trend in affinities of the anionic and neutral Lewis bases Cl− and HCl for the various cations. The Cl−X bond becomes longer and weaker along X+ = H+, CH3 +, Li+, and Na+. Our main purpose is to understand the heterolytic bonding mechanism behind the intrinsic (i.e., in the absence of solvent) alkali metal cation affinities (AMCA) and how this compares with and differs from those of the proton affinity (PA) and methyl cation affinity (MCA). Our analyses are based on Kohn–Sham molecular orbital (KS‐MO) theory in combination with a quantitative energy decomposition analysis (EDA) that pinpoints the importance of the different features in the bonding mechanism. Orbital overlap appears to play an important role in determining the trend in cation affinities. PMID:27551660

Structure-based approach to the prediction of disulfide bonds in proteins.

PubMed

Salam, Noeris K; Adzhigirey, Matvey; Sherman, Woody; Pearlman, David A

2014-10-01

Protein engineering remains an area of growing importance in pharmaceutical and biotechnology research. Stabilization of a folded protein conformation is a frequent goal in projects that deal with affinity optimization, enzyme design, protein construct design, and reducing the size of functional proteins. Indeed, it can be desirable to assess and improve protein stability in order to avoid liabilities such as aggregation, degradation, and immunogenic response that may arise during development. One way to stabilize a protein is through the introduction of disulfide bonds. Here, we describe a method to predict pairs of protein residues that can be mutated to form a disulfide bond. We combine a physics-based approach that incorporates implicit solvent molecular mechanics with a knowledge-based approach. We first assign relative weights to the terms that comprise our scoring function using a genetic algorithm applied to a set of 75 wild-type structures that each contains a disulfide bond. The method is then tested on a separate set of 13 engineered proteins comprising 15 artificial stabilizing disulfides introduced via site-directed mutagenesis. We find that the native disulfide in the wild-type proteins is scored well, on average (within the top 6% of the reasonable pairs of residues that could form a disulfide bond) while 6 out of the 15 artificial stabilizing disulfides scored within the top 13% of ranked predictions. Overall, this suggests that the physics-based approach presented here can be useful for triaging possible pairs of mutations for disulfide bond formation to improve protein stability. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Affinity proteomics to study endogenous protein complexes: Pointers, pitfalls, preferences and perspectives

PubMed Central

LaCava, John; Molloy, Kelly R.; Taylor, Martin S.; Domanski, Michal; Chait, Brian T.; Rout, Michael P.

2015-01-01

Dissecting and studying cellular systems requires the ability to specifically isolate distinct proteins along with the co-assembled constituents of their associated complexes. Affinity capture techniques leverage high affinity, high specificity reagents to target and capture proteins of interest along with specifically associated proteins from cell extracts. Affinity capture coupled to mass spectrometry (MS)-based proteomic analyses has enabled the isolation and characterization of a wide range of endogenous protein complexes. Here, we outline effective procedures for the affinity capture of protein complexes, highlighting best practices and common pitfalls. PMID:25757543

D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions

NASA Astrophysics Data System (ADS)

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A.; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2016-09-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

D3R Grand Challenge 2015: Evaluation of Protein-Ligand Pose and Affinity Predictions

PubMed Central

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2017-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (i) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (ii) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor. PMID:27696240

Adaptive Packet Combining Scheme in Three State Channel Model

NASA Astrophysics Data System (ADS)

Saring, Yang; Bulo, Yaka; Bhunia, Chandan Tilak

2018-01-01

The two popular techniques of packet combining based error correction schemes are: Packet Combining (PC) scheme and Aggressive Packet Combining (APC) scheme. PC scheme and APC scheme have their own merits and demerits; PC scheme has better throughput than APC scheme, but suffers from higher packet error rate than APC scheme. The wireless channel state changes all the time. Because of this random and time varying nature of wireless channel, individual application of SR ARQ scheme, PC scheme and APC scheme can't give desired levels of throughput. Better throughput can be achieved if appropriate transmission scheme is used based on the condition of channel. Based on this approach, adaptive packet combining scheme has been proposed to achieve better throughput. The proposed scheme adapts to the channel condition to carry out transmission using PC scheme, APC scheme and SR ARQ scheme to achieve better throughput. Experimentally, it was observed that the error correction capability and throughput of the proposed scheme was significantly better than that of SR ARQ scheme, PC scheme and APC scheme.

A New Approach to Develop Computer-aided Diagnosis Scheme of Breast Mass Classification Using Deep Learning Technology

PubMed Central

Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

2017-01-01

PURPOSE To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. RESULTS The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. CONCLUSIONS This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process. PMID:28436410

A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

PubMed

Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

2017-01-01

To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.

A Multiseason Comparison of the Forecast Skills among Three Numerical Models over Southcentral United States

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S.

2005-05-01

During the summer 2003 and winter 2003-2004, three mesoscale numerical models, the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), Navy's Coupled Ocean/Atmospheric Mesoscale Prediction System (COAMPS) and the Weather Research and Forecasting model (WRF), were operationally run at a horizontal resolution of 27 km twice daily in Jackson State University (JSU). Three models were run by the initial and lateral boundary conditions from AVN data. The purpose of this paper is to evaluate the performances of three models during these two seasons. It was found that the temporal variation of distribution and strength of mean error (ME) biases at 12, 24 and 36h was rather weak for surface temperature, sea level pressure and surface wind speed. During two seasons, the MM5 underpredicted the seasonal precipitation while the COAMPS and WRF overpredicted. This is consistent with the statistical score analyses of rainfall. The Bias scores revealed that the MM5 yielded an underprediction of precipitation, especially for heavier rainfall events. Due to the under estimate of rainfall areas and strength, the MM5 presented the lower TS, POD and KSS scores at lighter rainfall events compared to the COAMPS and WRF. At moderate to heavier thresholds, three models produced rather low KSS and POD scores that are consistent with the high FAR values. The WRF skills in predicting precipitation heavily depend on the performance of cumulus parameterization scheme. Instead of Kain-Fritsch scheme, using other two schemes, Grell-Devenyi and Bette-Miller-Janjic, in the WRF for warm season 2003 demonstrated that the precipitation overprediction had been efficiently suppressed. Overall, the performances of three models revealed that the best skill is at 12h and the worst at 36h.

Summary of evidence for an anticodonic basis for the origin of the genetic code

NASA Technical Reports Server (NTRS)

Lacey, J. C., Jr.; Mullins, D. W., Jr.

1981-01-01

This article summarizes data supporting the hypothesis that the genetic code origin was based on relationships (probably affinities) between amino acids and their anticodon nucleotides. Selective activation seems to follow from selective affinity and consequently, incorporation of amino acids into peptides can also be selective. It is suggested that these selectivities in affinity and activation, coupled with the base pairing specificities, allowed the origin of the code and the process of translation.

Affinity ranking of antibodies using flow cytometry: application in antibody phage display-based target discovery.

PubMed

Geuijen, Cecilia A W; Clijsters-van der Horst, Marieke; Cox, Freek; Rood, Pauline M L; Throsby, Mark; Jongeneelen, Mandy A C; Backus, Harold H J; van Deventer, Els; Kruisbeek, Ada M; Goudsmit, Jaap; de Kruif, John

2005-07-01

Application of antibody phage display to the identification of cell surface antigens with restricted expression patterns is often complicated by the inability to demonstrate specific binding to a certain cell type. The specificity of an antibody can only be properly assessed when the antibody is of sufficient high affinity to detect low-density antigens on cell surfaces. Therefore, a robust and simple assay for the prediction of relative antibody affinities was developed and compared to data obtained using surface plasmon resonance (SPR) technology. A panel of eight anti-CD46 antibody fragments with different affinities was selected from phage display libraries and reformatted into complete human IgG1 molecules. SPR was used to determine K(D) values for these antibodies. The association and dissociation of the antibodies for binding to CD46 expressed on cell surfaces were analysed using FACS-based assays. We show that ranking of the antibodies based on FACS data correlates well with ranking based on K(D) values as measured by SPR and can therefore be used to discriminate between high- and low-affinity antibodies. Finally, we show that a low-affinity antibody may only detect high expression levels of a surface marker while failing to detect lower expression levels of this molecule, which may lead to a false interpretation of antibody specificity.

SU-E-J-15: A Patient-Centered Scheme to Mitigate Impacts of Treatment Setup Error

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, L; Southern Medical University, Guangzhou; Tian, Z

2014-06-01

Purpose: Current Intensity Modulated Radiation Therapy (IMRT) is plan-centered. At each treatment fraction, we position the patient to match the setup in treatment plan. Inaccurate setup can compromise delivered dose distribution, and hence leading to suboptimal treatments. Moreover, current setup approach via couch shift under image guidance can correct translational errors, while rotational and deformation errors are hard to address. To overcome these problems, we propose in this abstract a patient-centered scheme to mitigate impacts of treatment setup errors. Methods: In the patient-centered scheme, we first position the patient on the couch approximately matching the planned-setup. Our Supercomputing Online Replanningmore » Environment (SCORE) is then employed to design an optimal treatment plan based on the daily patient geometry. It hence mitigates the impacts of treatment setup error and reduces the requirements on setup accuracy. We have conducted simulations studies in 10 head-and-neck (HN) patients to investigate the feasibility of this scheme. Rotational and deformation setup errors were simulated. Specifically, 1, 3, 5, 7 degrees of rotations were put on pitch, roll, and yaw directions; deformation errors were simulated by splitting neck movements into four basic types: rotation, lateral bending, flexion and extension. Setup variation ranges are based on observed numbers in previous studies. Dosimetric impacts of our scheme were evaluated on PTVs and OARs in comparison with original plan dose with original geometry and original plan recalculated dose with new setup geometries. Results: With conventional plan-centered approach, setup error could lead to significant PTV D99 decrease (−0.25∼+32.42%) and contralateral-parotid Dmean increase (−35.09∼+42.90%). The patientcentered approach is effective in mitigating such impacts to 0∼+0.20% and −0.03∼+5.01%, respectively. Computation time is <128 s. Conclusion: Patient-centered scheme is proposed to mitigate setup error impacts using replanning. Its superiority in terms of dosimetric impacts and feasibility has been shown through simulation studies on HN cases.« less

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

PubMed

Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance of tag set selection and the use of different tokenization strategies. Fine-grained tokenization combined with the tag set IOBES most effectively recognizes chemical and drug names. To the best of the authors' knowledge, this investigation is the first comprehensive investigation use of various tag set schemes combined with different tokenization strategies for the recognition of chemical entities.

Control of parallel manipulators using force feedback

NASA Technical Reports Server (NTRS)

Nanua, Prabjot

1994-01-01

Two control schemes are compared for parallel robotic mechanisms actuated by hydraulic cylinders. One scheme, the 'rate based scheme', uses the position and rate information only for feedback. The second scheme, the 'force based scheme' feeds back the force information also. The force control scheme is shown to improve the response over the rate control one. It is a simple constant gain control scheme better suited to parallel mechanisms. The force control scheme can be easily modified for the dynamic forces on the end effector. This paper presents the results of a computer simulation of both the rate and force control schemes. The gains in the force based scheme can be individually adjusted in all three directions, whereas the adjustment in just one direction of the rate based scheme directly affects the other two directions.

PREDICTING ER BINDING AFFINITY FOR EDC RANKING AND PRIORITIZATION: A COMPARISON OF THREE MODELS

EPA Science Inventory

A comparative analysis of how three COREPA models for ER binding affinity performed when used to predict potential estrogen receptor (ER) ligands is presented. Models I and II were developed based on training sets of 232 and 279 rat ER binding affinity measurements, respectively....

Response analysis in histopathology external quality assessment schemes.

PubMed

Furness, P N; Lauder, I

1993-04-01

To develop a computerised method for analysing the results of histopathology external quality assessment (EQA) schemes which can provide confidential personal reports to individual participating pathologists. A program was developed using the OMNIS database system, running on Apple Macintosh or IBM compatible computers. The program produces a general report of participants' responses to each case, and a choice of two types of personal report. One of these provides a list of the participant's diagnoses with a list of the most popular (Consensus) diagnoses for comparison. The other provides automatically calculated scores for the pathologist's performance along with simple statistical evaluation. The scores can be calculated by comparison with the consensus of the group or with correct diagnoses if they are known. A histogram indicating the distribution of performance within the group can be produced. The program can accept uncertainty in the form of differential diagnosis lists from participants. Potentially dangerous diagnostic errors can be identified and handled separately. Participants are identified only by code numbers and confidentiality can easily be enforced. The program is currently being used in the national renal pathology EQA scheme and in the local general histopathology scheme in the East Midlands. This program offers solutions to problems which have bedevilled the organisers of histopathology EQA schemes. It offers confidential advice to pathologists and will help to identify areas where an individual might benefit from continuing career grade medical education. It raises the possibility of the development of nationally agreed standards of performance in the reporting of pathological specimens, and it may be applicable to other specialties where textual reports are produced.

Somatostatin receptor immunohistochemistry in neuroendocrine tumors: comparison between manual and automated evaluation

PubMed Central

Daniel, Kaemmerer; Maria, Athelogou; Amelie, Lupp; Isabell, Lenhardt; Stefan, Schulz; Luisa, Peter; Merten, Hommann; Vikas, Prasad; Gerd, Binnig; Paul, Baum Richard

2014-01-01

Background: Manual evaluation of somatostatin receptor (SSTR) immunohistochemistry (IHC) is a time-consuming and cost-intensive procedure. Aim of the study was to compare manual evaluation of SSTR subtype IHC to an automated software-based analysis, and to in-vivo imaging by SSTR-based PET/CT. Methods: We examined 25 gastroenteropancreatic neuroendocrine tumor (GEP-NET) patients and correlated their in-vivo SSTR-PET/CT data (determined by the standardized uptake values SUVmax,-mean) with the corresponding ex-vivo IHC data of SSTR subtype (1, 2A, 4, 5) expression. Exactly the same lesions were imaged by PET/CT, resected and analyzed by IHC in each patient. After manual evaluation, the IHC slides were digitized and automatically evaluated for SSTR expression by Definiens XD software. A virtual IHC score “BB1” was created for comparing the manual and automated analysis of SSTR expression. Results: BB1 showed a significant correlation with the corresponding conventionally determined Her2/neu score of the SSTR-subtypes 2A (rs: 0.57), 4 (rs: 0.44) and 5 (rs: 0.43). BB1 of SSTR2A also significantly correlated with the SUVmax (rs: 0.41) and the SUVmean (rs: 0.50). Likewise, a significant correlation was seen between the conventionally evaluated SSTR2A status and the SUVmax (rs: 0.42) and SUVmean (rs: 0.62).Conclusion: Our data demonstrate that the evaluation of the SSTR status by automated analysis (BB1 score), using digitized histopathology slides (“virtual microscopy”), corresponds well with the SSTR2A, 4 and 5 expression as determined by conventional manual histopathology. The BB1 score also exhibited a significant association to the SSTR-PET/CT data in accordance with the high affinity profile of the SSTR analogues used for imaging. PMID:25197368

E-novo: an automated workflow for efficient structure-based lead optimization.

PubMed

Pearce, Bradley C; Langley, David R; Kang, Jia; Huang, Hongwei; Kulkarni, Amit

2009-07-01

An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.

Understanding the self-assembly of proteins onto gold nanoparticles and quantum dots driven by metal-histidine coordination.

PubMed

Aldeek, Fadi; Safi, Malak; Zhan, Naiqian; Palui, Goutam; Mattoussi, Hedi

2013-11-26

Coupling of polyhistidine-appended biomolecules to inorganic nanocrystals driven by metal-affinity interactions is a greatly promising strategy to form hybrid bioconjugates. It is simple to implement and can take advantage of the fact that polyhistidine-appended proteins and peptides are routinely prepared using well established molecular engineering techniques. A few groups have shown its effectiveness for coupling proteins onto Zn- or Cd-rich semiconductor quantum dots (QDs). Expanding this conjugation scheme to other metal-rich nanoparticles (NPs) such as AuNPs would be of great interest to researchers actively seeking effective means for interfacing nanostructured materials with biology. In this report, we investigated the metal-affinity driven self-assembly between AuNPs and two engineered proteins, a His7-appended maltose binding protein (MBP-His) and a fluorescent His6-terminated mCherry protein. In particular, we investigated the influence of the capping ligand affinity to the nanoparticle surface, its density, and its lateral extension on the AuNP-protein self-assembly. Affinity gel chromatography was used to test the AuNP-MPB-His7 self-assembly, while NP-to-mCherry-His6 binding was evaluated using fluorescence measurements. We also assessed the kinetics of the self-assembly between AuNPs and proteins in solution, using time-dependent changes in the energy transfer quenching of mCherry fluorescent proteins as they immobilize onto the AuNP surface. This allowed determination of the dissociation rate constant, Kd(-1) ∼ 1-5 nM. Furthermore, a close comparison of the protein self-assembly onto AuNPs or QDs provided additional insights into which parameters control the interactions between imidazoles and metal ions in these systems.

A Histopathological Scheme for the Quantitative Scoring of Intervertebral Disc Degeneration and the Therapeutic Utility of Adult Mesenchymal Stem Cells for Intervertebral Disc Regeneration

PubMed Central

Shu, Cindy C.; Smith, Margaret M.; Smith, Susan M.; Dart, Andrew J.; Little, Christopher B.; Melrose, James

2017-01-01

The purpose of this study was to develop a quantitative histopathological scoring scheme to evaluate disc degeneration and regeneration using an ovine annular lesion model of experimental disc degeneration. Toluidine blue and Haematoxylin and Eosin (H&E) staining were used to evaluate cellular morphology: (i) disc structure/lesion morphology; (ii) proteoglycan depletion; (iii) cellular morphology; (iv) blood vessel in-growth; (v) cell influx into lesion; and (vi) cystic degeneration/chondroid metaplasia. Three study groups were examined: 5 × 5 mm lesion; 6 × 20 mm lesion; and 6 × 20 mm lesion plus mesenchymal stem cell (MSC) treatment. Lumbar intervertebral discs (IVDs) were scored under categories (i–vi) to provide a cumulative score, which underwent statistical analysis using STATA software. Focal proteoglycan depletion was associated with 5 × 5 mm annular rim lesions, bifurcations, annular delamellation, concentric and radial annular tears and an early influx of blood vessels and cells around remodeling lesions but the inner lesion did not heal. Similar features in 6 × 20 mm lesions occurred over a 3–6-month post operative period. MSCs induced a strong recovery in discal pathology with a reduction in cumulative histopathology degeneracy score from 15.2 to 2.7 (p = 0.001) over a three-month recovery period but no recovery in carrier injected discs. PMID:28498326

A Histopathological Scheme for the Quantitative Scoring of Intervertebral Disc Degeneration and the Therapeutic Utility of Adult Mesenchymal Stem Cells for Intervertebral Disc Regeneration.

PubMed

Shu, Cindy C; Smith, Margaret M; Smith, Susan M; Dart, Andrew J; Little, Christopher B; Melrose, James

2017-05-12

The purpose of this study was to develop a quantitative histopathological scoring scheme to evaluate disc degeneration and regeneration using an ovine annular lesion model of experimental disc degeneration. Toluidine blue and Haematoxylin and Eosin (H&E) staining were used to evaluate cellular morphology: (i) disc structure/lesion morphology; (ii) proteoglycan depletion; (iii) cellular morphology; (iv) blood vessel in-growth; (v) cell influx into lesion; and (vi) cystic degeneration/chondroid metaplasia. Three study groups were examined: 5 × 5 mm lesion; 6 × 20 mm lesion; and 6 × 20 mm lesion plus mesenchymal stem cell (MSC) treatment. Lumbar intervertebral discs (IVDs) were scored under categories (i-vi) to provide a cumulative score, which underwent statistical analysis using STATA software. Focal proteoglycan depletion was associated with 5 × 5 mm annular rim lesions, bifurcations, annular delamellation, concentric and radial annular tears and an early influx of blood vessels and cells around remodeling lesions but the inner lesion did not heal. Similar features in 6 × 20 mm lesions occurred over a 3-6-month post operative period. MSCs induced a strong recovery in discal pathology with a reduction in cumulative histopathology degeneracy score from 15.2 to 2.7 ( p = 0.001) over a three-month recovery period but no recovery in carrier injected discs.

Effect on magnetic properties of germanium encapsulated C60 fullerene

NASA Astrophysics Data System (ADS)

Umran, Nibras Mossa; Kumar, Ranjan

2013-02-01

Structural and electronic properties of Gen(n = 1-4) doped C60 fullerene are investigated with ab initio density functional theory calculations by using an efficient computer code, known as SIESTA. The pseudopotentials are constructed using a Trouiller-Martins scheme, to describe the interaction of valence electrons with the atomic cores. In endohedral doped embedding of more germanium atoms complexes we have seen that complexes are stable and thereafter cage break down. We have also investigated that binding energy, electronic affinity increases and magnetic moment oscillating behavior as the number of semiconductor atoms in C60 fullerene goes on increasing.

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

Chemical Proteomics and Structural Biology Define EPHA2 Inhibition by Clinical Kinase Drugs.

PubMed

Heinzlmeir, Stephanie; Kudlinzki, Denis; Sreeramulu, Sridhar; Klaeger, Susan; Gande, Santosh Lakshmi; Linhard, Verena; Wilhelm, Mathias; Qiao, Huichao; Helm, Dominic; Ruprecht, Benjamin; Saxena, Krishna; Médard, Guillaume; Schwalbe, Harald; Kuster, Bernhard

2016-12-16

The receptor tyrosine kinase EPHA2 (Ephrin type-A receptor 2) plays important roles in oncogenesis, metastasis, and treatment resistance, yet therapeutic targeting, drug discovery, or investigation of EPHA2 biology is hampered by the lack of appropriate inhibitors and structural information. Here, we used chemical proteomics to survey 235 clinical kinase inhibitors for their kinase selectivity and identified 24 drugs with submicromolar affinities for EPHA2. NMR-based conformational dynamics together with nine new cocrystal structures delineated drug-EPHA2 interactions in full detail. The combination of selectivity profiling, structure determination, and kinome wide sequence alignment allowed the development of a classification system in which amino acids in the drug binding site of EPHA2 are categorized into key, scaffold, potency, and selectivity residues. This scheme should be generally applicable in kinase drug discovery, and we anticipate that the provided information will greatly facilitate the development of selective EPHA2 inhibitors in particular and the repurposing of clinical kinase inhibitors in general.

Accurate description of charged excitations in molecular solids from embedded many-body perturbation theory

NASA Astrophysics Data System (ADS)

Li, Jing; D'Avino, Gabriele; Duchemin, Ivan; Beljonne, David; Blase, Xavier

2018-01-01

We present a novel hybrid quantum/classical approach to the calculation of charged excitations in molecular solids based on the many-body Green's function G W formalism. Molecules described at the G W level are embedded into the crystalline environment modeled with an accurate classical polarizable scheme. This allows the calculation of electron addition and removal energies in the bulk and at crystal surfaces where charged excitations are probed in photoelectron experiments. By considering the paradigmatic case of pentacene and perfluoropentacene crystals, we discuss the different contributions from intermolecular interactions to electronic energy levels, distinguishing between polarization, which is accounted for combining quantum and classical polarizabilities, and crystal field effects, that can impact energy levels by up to ±0.6 eV. After introducing band dispersion, we achieve quantitative agreement (within 0.2 eV) on the ionization potential and electron affinity measured at pentacene and perfluoropentacene crystal surfaces characterized by standing molecules.

Mobilizing community-based health insurance to enhance awareness & prevention of airborne, vector-borne & waterborne diseases in rural India.

PubMed

Panda, Pradeep; Chakraborty, Arpita; Dror, David M

2015-08-01

Despite remarkable progress in airborne, vector-borne and waterborne diseases in India, the morbidity associated with these diseases is still high. Many of these diseases are controllable through awareness and preventive practice. This study was an attempt to evaluate the effectiveness of a preventive care awareness campaign in enhancing knowledge related with airborne, vector-borne and waterborne diseases, carried out in 2011 in three rural communities in India (Pratapgarh and Kanpur-Dehat in Uttar Pradesh and Vaishali in Bihar). Data for this analysis were collected from two surveys, one done before the campaign and the other after it, each of 300 randomly selected households drawn from a larger sample of Self-Help Groups (SHGs) members invited to join community-based health insurance (CBHI) schemes. The results showed a significant increase both in awareness (34%, p<0.001) and in preventive practices (48%, P=0.001), suggesting that the awareness campaign was effective. However, average practice scores (0.31) were substantially lower than average awareness scores (0.47), even in post-campaign. Awareness and preventive practices were less prevalent in vector-borne diseases than in airborne and waterborne diseases. Education was positively associated with both awareness and practice scores. The awareness scores were positive and significant determinants of the practice scores, both in the pre- and in the post-campaign results. Affiliation to CBHI had significant positive influence on awareness and on practice scores in the post-campaign period. The results suggest that well-crafted health educational campaigns can be effective in raising awareness and promoting health-enhancing practices in resource-poor settings. It also confirms that CBHI can serve as a platform to enhance awareness to risks of exposure to airborne, vector-borne and waterborne diseases, and encourage preventive practices.

[Role of hemoglobin affinity to oxygen in adaptation to hypoxemia].

PubMed

Kwasiborski, Przemysław Jerzy; Kowalczyk, Paweł; Zieliński, Jakub; Przybylski, Jacek; Cwetsch, Andrzej

2010-04-01

One of the basic mechanisms of adapting to hypoxemia is a decrease in the affinity of hemoglobin for oxygen. This process occurs mainly due to the increased synthesis of 2,3-diphosphoglycerate (2,3-DPG) in the erythrocytes, as well as through the Bohr effect. Hemoglobin with decreased affinity for oxygen increases the oxygenation of tissues, because it gives up oxygen more easily during microcirculation. In foetal circulation, however, at a partial oxygen pressure (pO2) of 25 mmHg in the umbilical vein, the oxygen carrier is type F hemoglobin which has a high oxygen affinity. The commonly accepted role for hemoglobin F is limited to facilitating diffusion through the placenta. Is fetal life the only moment when haemoglobin F is useful? THE AIM OF STUDY was to create a mathematical model, which would answer the question at what conditions an increase, rather than a decrease, in haemoglobin oxygen affinity is of benefit to the body. Using the kinetics of dissociation of oxygen from hemoglobin described by the Hill equation as the basis for further discussion, we created a mathematical model describing the pO2 value in the microcirculatory system and its dependence on arterial blood pO2. The calculations were performed for hemoglobin with low oxygen affinity (adult type) and high-affinity hemoglobin (fetal type). The modelling took into account both physiological and pathological ranges of acid-base equilibrium and tissue oxygen extraction parameters. It was shown that for the physiological range of acid-base equilibrium and the resting level of tissue oxygen extraction parameters, with an arterial blood pO2 of 26.8 mmHg, the higher-affinity hemoglobin becomes the more effective oxygen carrier. It was also demonstrated that the arterial blood pO2, below which the high-affinity hemoglobin becomes the more effective carrier, is dependent on blood pH and the difference between the arterial and venous oxygen saturation levels. Simulations performed for the pathological states showed that acidosis and increased tissue oxygen demand lead to a broadened arterial blood pO2 range, in which the high-affinity hemoglobin is more efficient. Contrary to the widely held view that the only response to hypoxemia is a decrease in haemoglobin oxygen affinity, it was shown that under extreme hypoxemic conditions, an increased haemoglobin oxygen affinity improves the oxygenation of tissues. It was also shown that the dominance of hemoglobin with a high oxygen affinity rapidly exceeds hemoglobin with low oxygen affinity in the case of acidosis with its accompanying high tissue oxygen extraction. In cases of extreme disruptions of the acid-base equilibrium, the dominance of high-oxygen-affinity hemoglobin spans over the entire possible range of pO2 in arterial blood.

Measuring moral hazard and adverse selection by propensity scoring in the mixed health care economy of Hong Kong.

PubMed

Wong, Irene O L; Lindner, Michael J; Cowling, Benjamin J; Lau, Eric H Y; Lo, Su-Vui; Leung, Gabriel M

2010-04-01

To evaluate the presence of moral hazard, adjusted for the propensity to have self-purchased insurance policies, employer-based medical benefits, and welfare-associated medical benefits in Hong Kong. Based on 2005 population survey, we used logistic regression and zero-truncated negative binomial/Poisson regressions to assess the presence of moral hazard by comparing inpatient and outpatient utilization between insured and uninsured individuals. We fitted each enabling factor specific to the type of service covered, and adjusted for predisposing socioeconomic and demographic factors. We used a propensity score approach to account for potential adverse selection. Employment-based benefits coverage was associated with increased access and intensity of use for both inpatient and outpatient care, except for public hospital use. Similarly, welfare-based coverage had comparable effect sizes as employment-based schemes, except for the total number of public ambulatory episodes. Self-purchased insurance facilitated access but did not apparently induce greater demand of services among ever users. Nevertheless, there was no evidence of moral hazard in public hospital use. Our findings suggest that employment-based benefits coverage lead to the greatest degree of moral hazard in Hong Kong. Future studies should focus on confirming these observational findings using a randomized design. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Applying a CAD-generated imaging marker to assess short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin

2018-02-01

Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (p<0.01). Thus, the study showed that CAD-generated false-positives might provide a new quantitative imaging marker to help assess short-term breast cancer risk.

(Z)-2-(3-Chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide as GSK-3β inhibitor: Identification by virtual screening and its validation in enzyme- and cell-based assay.

PubMed

Joshi, Prashant; Gupta, Mehak; Vishwakarma, Ram A; Kumar, Ajay; Bharate, Sandip B

2017-06-01

Glycogen synthase kinase 3β (GSK-3β) is a widely investigated molecular target for numerous diseases including Alzheimer's disease, cancer, and diabetes mellitus. The present study was aimed to discover new scaffolds for GSK-3β inhibition, through protein structure-guided virtual screening approach. With the availability of large number of GSK-3β crystal structures with varying degree of RMSD in protein backbone and RMSF in side chain geometry, herein appropriate crystal structures were selected based on the characteristic ROC curve and percentage enrichment of actives. The validated docking protocol was employed to screen a library of 50,000 small molecules using molecular docking and binding affinity calculations. Based on the GLIDE docking score, Prime MMGB/SA binding affinity, and interaction pattern analysis, the top 50 ligands were selected for GSK-3β inhibition. (Z)-2-(3-chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide (F389-0663, 7) was identified as a potent inhibitor of GSK-3β with an IC 50 value of 1.6 μm. Further, GSK-3β inhibition activity was then investigated in cell-based assay. The treatment of neuroblastoma N2a cells with 12.5 μm of F389-0663 resulted in the significant increase in GSK-3β Ser9 levels, which is indicative of the GSK-3β inhibitory activity of a compound. The molecular dynamic simulations were carried out to understand the interactions of F389-0663 with GSK-3β protein. © 2016 John Wiley & Sons A/S.

Design and Synthesis of High Affinity Inhibitors of Plasmodium falciparum and Plasmodium vivax N-Myristoyltransferases Directed by Ligand Efficiency Dependent Lipophilicity (LELP)

PubMed Central

2014-01-01

N-Myristoyltransferase (NMT) is an essential eukaryotic enzyme and an attractive drug target in parasitic infections such as malaria. We have previously reported that 2-(3-(piperidin-4-yloxy)benzo[b]thiophen-2-yl)-5-((1,3,5-trimethyl-1H-pyrazol-4-yl)methyl)-1,3,4-oxadiazole (34c) is a high affinity inhibitor of both Plasmodium falciparum and P. vivax NMT and displays activity in vivo against a rodent malaria model. Here we describe the discovery of 34c through optimization of a previously described series. Development, guided by targeting a ligand efficiency dependent lipophilicity (LELP) score of less than 10, yielded a 100-fold increase in enzyme affinity and a 100-fold drop in lipophilicity with the addition of only two heavy atoms. 34c was found to be equipotent on chloroquine-sensitive and -resistant cell lines and on both blood and liver stage forms of the parasite. These data further validate NMT as an exciting drug target in malaria and support 34c as an attractive tool for further optimization. PMID:24641010

Tensor scale-based fuzzy connectedness image segmentation

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Udupa, Jayaram K.

2003-05-01

Tangible solutions to image segmentation are vital in many medical imaging applications. Toward this goal, a framework based on fuzzy connectedness was developed in our laboratory. A fundamental notion called "affinity" - a local fuzzy hanging togetherness relation on voxels - determines the effectiveness of this segmentation framework in real applications. In this paper, we introduce the notion of "tensor scale" - a recently developed local morphometric parameter - in affinity definition and study its effectiveness. Although, our previous notion of "local scale" using the spherical model successfully incorporated local structure size into affinity and resulted in measureable improvements in segmentation results, a major limitation of the previous approach was that it ignored local structural orientation and anisotropy. The current approach of using tensor scale in affinity computation allows an effective utilization of local size, orientation, and ansiotropy in a unified manner. Tensor scale is used for computing both the homogeneity- and object-feature-based components of affinity. Preliminary results of the proposed method on several medical images and computer generated phantoms of realistic shapes are presented. Further extensions of this work are discussed.

A photo-cleavable biotin affinity tag for the facile release of a photo-crosslinked carbohydrate-binding protein.

PubMed

Chang, Tsung-Che; Adak, Avijit K; Lin, Ting-Wei; Li, Pei-Jhen; Chen, Yi-Ju; Lai, Chain-Hui; Liang, Chien-Fu; Chen, Yu-Ju; Lin, Chun-Cheng

2016-03-15

The use of photo-crosslinking glycoprobes represents a powerful strategy for the covalent capture of labile protein complexes and allows detailed characterization of carbohydrate-mediated interactions. The selective release of target proteins from solid support is a key step in functional proteomics. We envisaged that light activation can be exploited for releasing labeled protein in a dual photo-affinity probe-based strategy. To investigate this possibility, we designed a trifunctional, galactose-based, multivalent glycoprobe for affinity labeling of carbohydrate-binding proteins. The resulting covalent protein-probe adduct is attached to a photo-cleavable biotin affinity tag; the biotin moiety enables specific presentation of the conjugate on streptavidin-coated beads, and the photolabile linker allows the release of the labeled proteins. This dual probe promotes both the labeling and the facile cleavage of the target protein complexes from the solid surfaces and the remainder of the cell lysate in a completely unaltered form, thus eliminating many of the common pitfalls associated with traditional affinity-based purification methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiplexed Affinity-Based Separation of Proteins and Cells Using Inertial Microfluidics.

PubMed

Sarkar, Aniruddh; Hou, Han Wei; Mahan, Alison E; Han, Jongyoon; Alter, Galit

2016-03-30

Isolation of low abundance proteins or rare cells from complex mixtures, such as blood, is required for many diagnostic, therapeutic and research applications. Current affinity-based protein or cell separation methods use binary 'bind-elute' separations and are inefficient when applied to the isolation of multiple low-abundance proteins or cell types. We present a method for rapid and multiplexed, yet inexpensive, affinity-based isolation of both proteins and cells, using a size-coded mixture of multiple affinity-capture microbeads and an inertial microfluidic particle sorter device. In a single binding step, different targets-cells or proteins-bind to beads of different sizes, which are then sorted by flowing them through a spiral microfluidic channel. This technique performs continuous-flow, high throughput affinity-separation of milligram-scale protein samples or millions of cells in minutes after binding. We demonstrate the simultaneous isolation of multiple antibodies from serum and multiple cell types from peripheral blood mononuclear cells or whole blood. We use the technique to isolate low abundance antibodies specific to different HIV antigens and rare HIV-specific cells from blood obtained from HIV+ patients.

Determining ERβ Binding Affinity to Singly Mutant ERE Using Dual Polarization Interferometry

NASA Astrophysics Data System (ADS)

Song, Hong Yan; Su, Xiaodi

In a classic mode of estrogen action, estrogen receptors (ERs) bind to estrogen responsive element (ERE) to activate gene transcription. A perfect ERE contains a 13-base pair sequence of a palindromic repeat separated by a three-base spacer, 5‧-GGTCAnnnTGACC-3‧. In addition to the consensus or wild-type ERE (wtERE), naturally occurring EREs often have one or two base pairs’ alternation. Based on the newly constructed Thermodynamic Modeling of ChIP-seq (TherMos) model, binding energy between ERβ and a series of 34-bp mutant EREs (mutERE) was simulated to predict the binding affinity between ERs and EREs with single base pair deviation at different sites of the 13-bp inverted sequence. Experimentally, dual polarization interferometry (DPI) method was developed to measure ERβ-mutEREs binding affinity. On a biotin-NeutrAvidin (NA)-biotin treated DPI chip, wtERE is immobilized. In a direct binding assay, ERβ-wtERE binding affinity is determined. In a competition assay, ERβ was preincubated with mutant EREs before being added for competitive binding to the immobilized wtERE. This competition strategy provided a successful platform to evaluate the binding affinity variation among large number of ERE with different base mutations. The experimental result correlates well with the mathematically predicted binding energy with a Spearman correlation coefficient of 0.97.

Investigation of MM-PBSA rescoring of docking poses.

PubMed

Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane

2008-05-01

Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.

A HIGH-LEVEL CALCULATION OF THE PROTON AFFINITY OF DIBORANE

EPA Science Inventory

The experimental proton affinity of diborane (B2H6) is based on an unstable species, B2H,+, 4 which has been observed only at low temperatures. The present work calculates the proton 5 affinity of diborane using the Gaussian-3 method and other high-level compound ab initio 6 met...

GDPC: Gravitation-based Density Peaks Clustering algorithm

NASA Astrophysics Data System (ADS)

Jiang, Jianhua; Hao, Dehao; Chen, Yujun; Parmar, Milan; Li, Keqin

2018-07-01

The Density Peaks Clustering algorithm, which we refer to as DPC, is a novel and efficient density-based clustering approach, and it is published in Science in 2014. The DPC has advantages of discovering clusters with varying sizes and varying densities, but has some limitations of detecting the number of clusters and identifying anomalies. We develop an enhanced algorithm with an alternative decision graph based on gravitation theory and nearby distance to identify centroids and anomalies accurately. We apply our method to some UCI and synthetic data sets. We report comparative clustering performances using F-Measure and 2-dimensional vision. We also compare our method to other clustering algorithms, such as K-Means, Affinity Propagation (AP) and DPC. We present F-Measure scores and clustering accuracies of our GDPC algorithm compared to K-Means, AP and DPC on different data sets. We show that the GDPC has the superior performance in its capability of: (1) detecting the number of clusters obviously; (2) aggregating clusters with varying sizes, varying densities efficiently; (3) identifying anomalies accurately.

Literature-based concept profiles for gene annotation: the issue of weighting.

PubMed

Jelier, Rob; Schuemie, Martijn J; Roes, Peter-Jan; van Mulligen, Erik M; Kors, Jan A

2008-05-01

Text-mining has been used to link biomedical concepts, such as genes or biological processes, to each other for annotation purposes or the generation of new hypotheses. To relate two concepts to each other several authors have used the vector space model, as vectors can be compared efficiently and transparently. Using this model, a concept is characterized by a list of associated concepts, together with weights that indicate the strength of the association. The associated concepts in the vectors and their weights are derived from a set of documents linked to the concept of interest. An important issue with this approach is the determination of the weights of the associated concepts. Various schemes have been proposed to determine these weights, but no comparative studies of the different approaches are available. Here we compare several weighting approaches in a large scale classification experiment. Three different techniques were evaluated: (1) weighting based on averaging, an empirical approach; (2) the log likelihood ratio, a test-based measure; (3) the uncertainty coefficient, an information-theory based measure. The weighting schemes were applied in a system that annotates genes with Gene Ontology codes. As the gold standard for our study we used the annotations provided by the Gene Ontology Annotation project. Classification performance was evaluated by means of the receiver operating characteristics (ROC) curve using the area under the curve (AUC) as the measure of performance. All methods performed well with median AUC scores greater than 0.84, and scored considerably higher than a binary approach without any weighting. Especially for the more specific Gene Ontology codes excellent performance was observed. The differences between the methods were small when considering the whole experiment. However, the number of documents that were linked to a concept proved to be an important variable. When larger amounts of texts were available for the generation of the concepts' vectors, the performance of the methods diverged considerably, with the uncertainty coefficient then outperforming the two other methods.

Nonadiabatic ab initio molecular dynamics with PME-ONIOM scheme of photoisomerization reaction between 1,3-cyclohexadiene and 1,3,5-cis-hexatriene in solution phase

NASA Astrophysics Data System (ADS)

Ohta, Ayumi; Kobayashi, Osamu; Danielache, Sebastian O.; Nanbu, Shinkoh

2017-03-01

The ultra-fast photoisomerization reactions between 1,3-cyclohexadiene (CHD) and 1,3,5-cis-hexatriene (HT) in both hexane and ethanol solvents were revealed by nonadiabatic ab initio molecular dynamics (AI-MD) with a particle-mesh Ewald summation method and our Own N-layered Integrated molecular Orbital and molecular Mechanics model (PME-ONIOM) scheme. Zhu-Nakamura version trajectory surface hopping method (ZN-TSH) was employed to treat the ultra-fast nonadiabatic decaying process. The results for hexane and ethanol simulations reasonably agree with experimental data. The high nonpolar-nonpolar affinity between CHD and the solvent was observed in hexane solvent, which definitely affected the excited state lifetimes, the product branching ratio of CHD:HT, and solute (CHD) dynamics. In ethanol solvent, however, the CHD solute was isomerized in the solvent cage caused by the first solvation shell. The photochemical dynamics in ethanol solvent results in the similar property to the process appeared in vacuo (isolated CHD dynamics).

When Middle Really Means "Top" or "Bottom": An Analysis of the 16PF5 Using Bock's Nominal Response Model.

PubMed

Murray, Aja Louise; Booth, Tom; Molenaar, Dylan

2016-01-01

When self-report items with a Likert-type scale include a middle response option (e.g., Unsure, Neither agree nor disagree, or ?), this middle option is assumed to measure a level of the trait intermediate between the high and low response categories. In this study, we tested this assumption in the 16 Personality Factor Questionnaire, Version 5 (16PF5) by fitting Bock's nominal response model in the U.S. and UK standardization samples of the 16PF5. We found that in many cases, the middle option was indicative of higher levels of the latent trait than the ostensibly highest response option. In certain other cases, it was indicative of lower levels of the latent trait than the ostensibly lowest response option. This undermines the use of a simple successive integer scoring scheme where responses in adjacent response categories are assigned scores of 0, 1, and 2. Recommendations for alternative scoring schemes are provided. Results also suggested that certain personality traits, especially neurotic traits, are associated with a tendency toward selecting the middle option.

Unavailability of thymidine kinase does not preclude the use of German comprehensive prognostic index: results of an external validation analysis in early chronic lymphocytic leukemia and comparison with MD Anderson Cancer Center model.

PubMed

Molica, Stefano; Giannarelli, Diana; Mirabelli, Rosanna; Levato, Luciano; Russo, Antonio; Linardi, Maria; Gentile, Massimo; Morabito, Fortunato

2016-01-01

A comprehensive prognostic index that includes clinical (i.e., age, sex, ECOG performance status), serum (i.e., ß2-microglobulin, thymidine kinase [TK]), and molecular (i.e., IGVH mutational status, del 17p, del 11q) markers developed by the German CLL Study Group (GCLLSG) was externally validated in a prospective, community-based cohort consisting of 338 patients with early chronic lymphocytic leukemia (CLL) using as endpoint the time to first treatment (TTFT). Because serum TK was not available, a slightly modified version of the model based on seven instead of eight prognostic variables was used. By German index, 62.9% of patients were scored as having low-risk CLL (score 0-2), whereas 37.1% had intermediate-risk CLL (score 3-5). This stratification translated into a significant difference in the TTFT [HR = 4.21; 95% C.I. (2.71-6.53); P < 0.0001]. Also the 2007 MD Anderson Cancer Center (MDACC) score, barely based on traditional clinical parameters, showed comparable reliability [HR = 2.73; 95% C.I. (1.79-4.17); P < 0.0001]. A comparative performance assessment between the two models revealed that prediction of the TTFT was more accurate with German score. The c-statistic of the MDACC model was 0.65 (range, 0.53-0.78) a level below that of the German index [0.71 (range, 0.60-0.82)] and below the accepted 0.7 threshold necessary to have value at the individual patient level. Results of this external comparative validation analysis strongly support the German score as the benchmark for comparison of any novel prognostic scheme aimed at evaluating the TTFT in patients with early CLL even when a modified version which does not include TK is utilized. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Cytomegalovirus-Specific CD8+ T-Cells With Different T-Cell Receptor Affinities Segregate T-Cell Phenotypes and Correlate With Chronic Graft-Versus-Host Disease in Patients Post-Hematopoietic Stem Cell Transplantation

PubMed Central

Poiret, Thomas; Axelsson-Robertson, Rebecca; Remberger, Mats; Luo, Xiao-Hua; Rao, Martin; Nagchowdhury, Anurupa; Von Landenberg, Anna; Ernberg, Ingemar; Ringden, Olle; Maeurer, Markus

2018-01-01

Virus-specific T-cell responses are crucial to control cytomegalovirus (CMV) infections/reactivation in immunocompromised individuals. Adoptive cellular therapy with CMV-specific T-cells has become a viable treatment option. High-affinity anti-viral cellular immune responses are associated with improved long-term immune protection against CMV infection. To date, the characterization of high-affinity T-cell responses against CMV has not been achieved in blood from patients after allogeneic hematopoietic stem cell transplantation (HSCT). Therefore, the purpose of this study was to describe and analyze the phenotype and clinical impact of different CMV-specific CD8+ cytotoxic T-lymphocytes (CMV-CTL) classes based on their T-cell receptor (TCR) affinity. T-cells isolated from 23 patients during the first year following HSCT were tested for the expression of memory markers, programmed cell death 1 (PD-1), as well as TCR affinity, using three different HLA-A*02:01 CMVNLVPMVATV-Pp65 tetramers (wild-type, a245v and q226a mutants). High-affinity CMV-CTL defined by q226a tetramer binding, exhibited a higher frequency in CD8+ T-cells in the first month post-HSCT and exhibited an effector memory phenotype associated with strong PD-1 expression as compared to the medium- and low-affinity CMV-CTLs. High-affinity CMV-CTL was found at higher proportion in patients with chronic graft-versus-host disease (p < 0.001). This study provides a first insight into the detailed TCR affinities of CMV-CTL. This may be useful in order to improve current immunotherapy protocols using isolation of viral-specific T-cell populations based on their TCR affinity. PMID:29692783

The Power of Reflective Professional Development in Changing Elementary School Teachers' Instructional Practices

NASA Astrophysics Data System (ADS)

Cavedon, Carolina Christmann

With the new goal of K-12 education being to prepare students to be college and career ready at the end of high school, education needs to start changing at the elementary school level. The literature suggests that teachers need reflective professional development (PD) to effectively teach to the new standards and to demonstrate change to their current instructional practices. This mixed-method multiple-case study investigated the impacts of a reflective professional development (PD) in changing elementary school teachers' instructional practices. Teachers Instructional Portfolios (TIPs) were scored with a TIP rubric based on best practices in teaching mathematics problem-solving and science inquiry. The TIPs were also analyzed with a qualitative coding scheme. Case descriptions were written and all the collected data were used to explain the impacts of the reflective PD on changes in teachers' instructional practices. While we found no predictive patterns in relation to teachers changing their classroom practices based on the reflective PD, we claim that teachers' desire to change might contribute to improvements in instruction. We also observed that teachers' self-assessment scores tend to be higher than the actual TIP scores corroborating with the literature on the usage of self-assessment to evaluate teachers' instructional practices.

Ranking of tree-ring based temperature reconstructions of the past millennium

NASA Astrophysics Data System (ADS)

Esper, Jan; Krusic, Paul J.; Ljungqvist, Fredrik C.; Luterbacher, Jürg; Carrer, Marco; Cook, Ed; Davi, Nicole K.; Hartl-Meier, Claudia; Kirdyanov, Alexander; Konter, Oliver; Myglan, Vladimir; Timonen, Mauri; Treydte, Kerstin; Trouet, Valerie; Villalba, Ricardo; Yang, Bao; Büntgen, Ulf

2016-08-01

Tree-ring chronologies are widely used to reconstruct high-to low-frequency variations in growing season temperatures over centuries to millennia. The relevance of these timeseries in large-scale climate reconstructions is often determined by the strength of their correlation against instrumental temperature data. However, this single criterion ignores several important quantitative and qualitative characteristics of tree-ring chronologies. Those characteristics are (i) data homogeneity, (ii) sample replication, (iii) growth coherence, (iv) chronology development, and (v) climate signal including the correlation with instrumental data. Based on these 5 characteristics, a reconstruction-scoring scheme is proposed and applied to 39 published, millennial-length temperature reconstructions from Asia, Europe, North America, and the Southern Hemisphere. Results reveal no reconstruction scores highest in every category and each has their own strengths and weaknesses. Reconstructions that perform better overall include N-Scan and Finland from Europe, E-Canada from North America, Yamal and Dzhelo from Asia. Reconstructions performing less well include W-Himalaya and Karakorum from Asia, Tatra and S-Finland from Europe, and Great Basin from North America. By providing a comprehensive set of criteria to evaluate tree-ring chronologies we hope to improve the development of large-scale temperature reconstructions spanning the past millennium. All reconstructions and their corresponding scores are provided at http://www.blogs.uni-mainz.de/fb09climatology.

Scoring functions for protein-protein interactions.

PubMed

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Clinically relevant advances in on-chip affinity-based electrophoresis and electrochromatography.

PubMed

Hou, Chenlu; Herr, Amy E

2008-08-01

Clinical and point-of-care disease diagnostics promise to play an important role in personalized medicine, new approaches to global health, and health monitoring. Emerging instrument platforms based on lab-on-a-chip technology can confer performance advantages successfully exploited in electrophoresis and electrochromatography to affinity-based electrokinetic separations. This review surveys lab-on-a-chip diagnostic developments in affinity-based electrokinetic separations for quantitation of proteins, integration of preparatory functions needed for subsequent analysis of diverse biological samples, and initial forays into multiplexed analyses. The technologies detailed here underpin new clinical and point-of-care diagnostic strategies. The techniques and devices promise to advance translation of until now laboratory-based sample preparation and analytical assays to near-patient settings.

Influence of bulk microphysics schemes upon Weather Research and Forecasting (WRF) version 3.6.1 nor'easter simulations

NASA Astrophysics Data System (ADS)

Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen I.

2017-03-01

This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 h prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217-0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude diagrams (CFADs) reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

Influence of Bulk Microphysics Schemes upon Weather Research and Forecasting (WRF) Version 3.6.1 Nor'easter Simulations.

PubMed

Nicholls, Stephen D; Decker, Steven G; Tao, Wei-Kuo; Lang, Stephen E; Shi, Jainn J; Mohr, Karen I

2017-01-01

This study evaluated the impact of five, single- or double- moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven, intense winter time cyclones impacting the Mid-Atlantic United States. Five-day long WRF simulations were initialized roughly 24 hours prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (5 BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities lead to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatio-temporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF-simulations demonstrate low-to-moderate (0.217-0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude (CFAD) diagrams reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

Influence of Bulk Microphysics Schemes upon Weather Research and Forecasting (WRF) Version 3.6.1 Nor'easter Simulations

PubMed Central

Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen I.

2018-01-01

This study evaluated the impact of five, single- or double- moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven, intense winter time cyclones impacting the Mid-Atlantic United States. Five-day long WRF simulations were initialized roughly 24 hours prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (5 BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities lead to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatio-temporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF-simulations demonstrate low-to-moderate (0.217–0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude (CFAD) diagrams reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions. PMID:29697705

Influence of Bulk Microphysics Schemes upon Weather Research and Forecasting (WRF) Version 3.6.1 Nor'easter Simulations

NASA Technical Reports Server (NTRS)

Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen Irene

2017-01-01

This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 hours prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217 to 0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude (CFAD) diagrams reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

Sense and simplicity in HADDOCK scoring: Lessons from CASP‐CAPRI round 1

PubMed Central

Vangone, A.; Rodrigues, J. P. G. L. M.; Xue, L. C.; van Zundert, G. C. P.; Geng, C.; Kurkcuoglu, Z.; Nellen, M.; Narasimhan, S.; Karaca, E.; van Dijk, M.; Melquiond, A. S. J.; Visscher, K. M.; Trellet, M.; Kastritis, P. L.

2016-01-01

ABSTRACT Our information‐driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community‐wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP‐CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets – a top‐ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico‐chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center‐of‐mass and symmetry restrained protocol, or on a template‐based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417–423. © 2016 Wiley Periodicals, Inc. PMID:27802573

Choices in the use of ICD-9 codes to identify stroke risk factors can affect the apparent population-level risk factor prevalence and distribution of CHADS2 scores

PubMed Central

Rothendler, James A; Rose, Adam J; Reisman, Joel I; Berlowitz, Dan R; Kazis, Lewis E

2012-01-01

While developed for managing individuals with atrial fibrillation, risk stratification schemes for stroke, such as CHADS2, may be useful in population-based studies, including those assessing process of care. We investigated how certain decisions in identifying diagnoses from administrative data affect the apparent prevalence of CHADS2-associated diagnoses and distribution of scores. Two sets of ICD-9 codes (more restrictive/ more inclusive) were defined for each CHADS2-associated diagnosis. For stroke/transient ischemic attack (TIA), the more restrictive set was applied to only inpatient data. We varied the number of years (1-3) in searching for relevant codes, and, except for stroke/TIA, the number of instances (1 vs. 2) that diagnoses were required to appear. The impact of choices on apparent disease prevalence varied by type of choice and condition, but was often substantial. Choices resulting in substantial changes in prevalence also tended to be associated with more substantial effects on the distribution of CHADS2 scores. PMID:22937488

Sarizotan as a treatment for dyskinesias in Parkinson's disease: a double-blind placebo-controlled trial.

PubMed

Goetz, Christopher G; Damier, Philippe; Hicking, Christine; Laska, Eugene; Müller, Thomas; Olanow, C Warren; Rascol, Olivier; Russ, Hermann

2007-01-15

The objective of this study is to conduct a dose-finding study of sarizotan in Parkinson's disease (PD) patients with dyskinesia to identify a safe dose and to identify a sensitive dyskinesia rating measure. Sarizotan is a novel compound with full 5-HT(1A) agonist properties and additional high affinity for D(3) and D(4) receptors. An open label study documented improvements in PD patients with levodopa-induced dyskinesia. There is no precedent for study designs or outcome measures in pivotal trials of antidyskinesia therapies. The approach used here was a multicenter, randomized, placebo-controlled, double-blind, parallel study. Included were PD patients optimized to levodopa and dopaminergic drugs with moderately disabling dyskinesias present greater than or equal to 25% of the waking day. Interventions included sarizotan 2, 4, or 10 mg/day or matching placebo, given in two doses. There were two outcome measures: the primary measure was change from baseline in diary-based on time without dyskinesia; the secondary measures were change from baseline in scores on the Abnormal Involuntary Movement Scale (AIMS), the composite score of Unified Parkinson's Disease Rating Scale (UPDRS) Items 32+33 (dyskinesia duration and disability) and total UPDRS. A total of 398 subjects were randomized, with 381 included in the intention-to-treat population. No significant changes occurred on sarizotan compared to placebo on any diary-based measure of dyskinesia or the AIMS score. The composite score of UPDRS Items 32+33 was significantly improved with 2 mg/day sarizotan, with a trend at 10 mg/day. Adverse events were not significantly different in sarizotan- and placebo-treated patients, but off time significantly increased with sarizotan 10 mg/day. Sarizotan 2 mg/day is a safe agent in PD patients with dyskinesia. To test its role in abating dyskinesia, future studies should focus on this dose and will use the composite score of UPDRS Items 32+33 as the primary outcome. (c) 2006 Movement Disorder Society.

Combinatorial approaches to gene recognition.

PubMed

Roytberg, M A; Astakhova, T V; Gelfand, M S

1997-01-01

Recognition of genes via exon assembly approaches leads naturally to the use of dynamic programming. We consider the general graph-theoretical formulation of the exon assembly problem and analyze in detail some specific variants: multicriterial optimization in the case of non-linear gene-scoring functions; context-dependent schemes for scoring exons and related procedures for exon filtering; and highly specific recognition of arbitrary gene segments, oligonucleotide probes and polymerase chain reaction (PCR) primers.

Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach.

PubMed

Katiyar, Prateek; Divine, Mathew R; Kohlhofer, Ursula; Quintanilla-Martinez, Leticia; Schölkopf, Bernhard; Pichler, Bernd J; Disselhorst, Jonathan A

2017-04-01

In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18 F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18 F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18 F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18 F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor heterogeneity using dynamic PET studies. Because SC tumor segmentation is based on the intrinsic structure of the underlying data, it can be easily applied to other cancer types as well. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Proton Affinities of Anionic Bases:  Trends Across the Periodic Table, Structural Effects, and DFT Validation.

PubMed

Swart, Marcel; Bickelhaupt, F Matthias

2006-03-01

We have carried out an extensive exploration of the gas-phase basicity of archetypal anionic bases across the periodic system using the generalized gradient approximation of density functional theory (DFT) at BP86/QZ4P//BP86/TZ2P. First, we validate DFT as a reliable tool for computing proton affinities and related thermochemical quantities:  BP86/QZ4P//BP86/TZ2P is shown to yield a mean absolute deviation of 1.6 kcal/mol for the proton affinity at 0 K with respect to high-level ab initio benchmark data. The main purpose of this work is to provide the proton affinities (and corresponding entropies) at 298 K of the anionic conjugate bases of all main-group-element hydrides of groups 14-17 and periods 2-6. We have also studied the effect of stepwise methylation of the protophilic center of the second- and third-period bases.

An ellipsoidal calculus based on propagation and fusion.

PubMed

Ros, L; Sabater, A; Thomas, F

2002-01-01

Presents an ellipsoidal calculus based solely on two basic operations: propagation and fusion. Propagation refers to the problem of obtaining an ellipsoid that must satisfy an affine relation with another ellipsoid, and fusion to that of computing the ellipsoid that tightly bounds the intersection of two given ellipsoids. These two operations supersede the Minkowski sum and difference, affine transformation and intersection tight bounding of ellipsoids on which other ellipsoidal calculi are based. Actually, a Minkowski operation can be seen as a fusion followed by a propagation and an affine transformation as a particular case of propagation. Moreover, the presented formulation is numerically stable in the sense that it is immune to degeneracies of the involved ellipsoids and/or affine relations. Examples arising when manipulating uncertain geometric information in the context of the spatial interpretation of line drawings are extensively used as a testbed for the presented calculus.

Interaction of antithrombin with sulfated, low molecular weight lignins: opportunities for potent, selective modulation of antithrombin function.

PubMed

Henry, Brian L; Connell, Justin; Liang, Aiye; Krishnasamy, Chandravel; Desai, Umesh R

2009-07-31

Antithrombin, a major regulator of coagulation and angiogenesis, is known to interact with several natural sulfated polysaccharides. Previously, we prepared sulfated low molecular weight variants of natural lignins, called sulfated dehydrogenation polymers (DHPs) (Henry, B. L., Monien, B. H., Bock, P. E., and Desai, U. R. (2007) J. Biol. Chem. 282, 31891-31899), which have now been found to exhibit interesting antithrombin binding properties. Sulfated DHPs represent a library of diverse noncarbohydrate aromatic scaffolds that possess structures completely different from heparin and heparan sulfate. Fluorescence binding studies indicate that sulfated DHPs bind to antithrombin with micromolar affinity under physiological conditions. Salt dependence of binding affinity indicates that the antithrombin-sulfated DHP interaction involves a massive 80-87% non-ionic component to the free energy of binding. Competitive binding studies with heparin pentasaccharide, epicatechin sulfate, and full-length heparin indicate that sulfated DHPs bind to both the pentasaccharide-binding site and extended heparin-binding site of antithrombin. Affinity capillary electrophoresis resolves a limited number of peaks of antithrombin co-complexes suggesting preferential binding of selected DHP structures to the serpin. Computational genetic algorithm-based virtual screening study shows that only one sulfated DHP structure, out of the 11 present in a library of plausible sequences, bound in the heparin-binding site with a high calculated score supporting selectivity of recognition. Enzyme inhibition studies indicate that only one of the three sulfated DHPs studied is a potent inhibitor of free factor VIIa in the presence of antithrombin. Overall, the chemo-enzymatic origin and antithrombin binding properties of sulfated DHPs present novel opportunities for potent and selective modulation of the serpin function, especially for inhibiting the initiation phase of hemostasis.

Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

NASA Astrophysics Data System (ADS)

He, Qiang; Schultz, Richard R.; Wang, Yi; Camargo, Aldo; Martel, Florent

2008-01-01

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

Pushing antibody-based labeling systems to higher sensitivity by linker-assisted affinity enhancement.

PubMed

Gorris, Hans H; Bade, Steffen; Röckendorf, Niels; Fránek, Milan; Frey, Andreas

2011-08-17

The sensitivity of antibody/hapten-based labeling systems is limited by the natural affinity ceiling of immunoglobulins. Breaking this limit by antibody engineering is difficult. We thus attempted a different approach and investigated if the so-called bridge effect, a corecognition of the linker present between hapten and carrier protein during antibody generation, can be utilized to improve the affinity of such labeling systems. The well-known haptens 2,4-dinitrophenol (2,4-DNP) and 2,4-dichlorophenoxyacetic acid (2,4-D) were equipped with various linkers, and the resulting affinity change of their cognate antibodies was analyzed by ELISA. Anti-2,4-DNP antibodies exhibited the best affinity to their hapten when it was combined with aminobutanoic acid or aminohexanoic acid. The affinity of anti-2,4-D antibodies could be enhanced even further with longer aliphatic spacers connected to the hapten. The affinity toward aminoundecanoic acid-2,4-D derivatives, for instance, was improved about 100-fold compared to 2,4-D alone and yielded detection limits as low as 100 amoles of analyte. As the effect occurred for all antibodies and haptens tested, it may be sensible to implement the bridge effect in future antibody/hapten-labeling systems in order to achieve the highest sensitivity possible.

The best prostate biopsy scheme is dictated by the gland volume: a monocentric study.

PubMed

Dell'Atti, L

2015-08-01

Accuracy of biopsy scheme depends on different parameters. Prostate-specific antigen (PSA) level and digital rectal examination (DRE) influenced the detection rate and suggested the biopsy scheme to approach each patient. Another parameter is the prostate volume. Sampling accuracy tends to decrease progressively with an increasing prostate volume. We prospectively observed detection cancer rate in suspicious prostate cancer (PCa) and improved by applying a protocol biopsy according to prostate volume (PV). Clinical data and pathological features of these 1356 patients were analysed and included in this study. This protocol is a combined scheme that includes transrectal (TR) 12-core PBx (TR12PBx) for PV ≤ 30 cc, TR 14-core PBx (TR14PBx) for PV > 30 cc but < 60 cc, TR 18-core PBx (TR18PBx) for PV ≥ 60 cc. Out of a total of 1356 patients, in 111 (8.2%) PCa was identified through TR12PBx scheme, in 198 (14.6%) through TR14PBx scheme and in 253 (18.6%) through TR18PBx scheme. The PCa detection rate was increased by 44% by adding two TZ cores (TR14PBx scheme). The TR18PBx scheme increased this rate by 21.7% vs. TR14PBx scheme. The diagnostic yield offered by TR18PBx was statistically significant compared to the detection rate offered by the TR14PBx scheme (p < 0.003). The biopsy Gleason score and the percentage of core involvement were comparable between PCa detected by the TR14PBx scheme diagnostic yield and those detected by the TR18PBx scheme (p = 0.362). The only PV parameter, in our opinion, can be significant in choosing the best biopsy scheme to approach in a first setting of biopsies increasing PCa detection rate.

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

PubMed

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

Shedding Light on Learning.

ERIC Educational Resources Information Center

Graves, Ben E.

1985-01-01

Summarizes findings of an Alberta light/color study that looked at mood, noise levels, IQ test scores, blood pressure, and absences under fluorescent or full-spectrum light in two color schemes in four elementary schools with 700 students. (MLF)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Qibin; Tang, Ning; Brock, Jonathan W.

Non-enzymatic glycation of peptides and proteins by D-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. It was observed that ETD fragmentation mode resultedmore » in a significantly higher number of glycated peptide identifications (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing dual glycation enrichment on both the protein and peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS with ETD as the fragmentation mode is an efficient approach for analyses of glycated proteins and can have broad applications in studies of diabetes mellitus.« less

Targeting Anti-Cancer Active Compounds: Affinity-Based Chromatographic Assays

PubMed Central

de Moraes, Marcela Cristina; Cardoso, Carmen Lucia; Seidl, Claudia; Moaddel, Ruin; Cass, Quezia Bezerra

2016-01-01

Affinity-based chromatography assays encompass the use of solid supports containing immobilized biological targets to monitor binding events in the isolation , identification and/or characterization of bioactive compounds. This powerful bioanalytical technique allows the screening of potential binders through fast analyses that can be directly performed using isolated substances or complex matrices. An overview of the recent researches in frontal and zonal affinity-based chromatography screening assays, which has been used as a tool in the identification and characterization of new anti-cancer agents, is discussed. In addition, a critical evaluation of the recently emerged ligands fishing assays in complex mixtures is also discussed. PMID:27306095

A Kalman Filtering Perspective for Multiatlas Segmentation*

PubMed Central

Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

2016-01-01

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

istar: a web platform for large-scale protein-ligand docking.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Ballester, Pedro J; Wong, Man-Hon

2014-01-01

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.

Investigating the DSM-5 severity specifiers based on thinness for adults with anorexia nervosa.

PubMed

Reas, Deborah Lynn; Rø, Øyvind

2017-08-01

The DSM-5 severity classification scheme for adults with anorexia nervosa (AN) is based upon current body mass index (BMI; kg/m 2 ). This study examined the utility of the DSM-5 severity specifiers for adults with AN in relation to core cognitive and behavioral features of eating pathology and associated psychosocial impairment. A clinical sample of 146 adult AN patients (140 women, 6 men) were categorized using DSM-5 current BMI severity specifiers and assessed with the Eating Disorder Examination-Questionnaire (EDE-Q) and Clinical Impairment Assessment (CIA). A total of 34 (23.3%) patients were categorized as mild (>=17.0 BMI), 35 (24.0%) as moderate (16-16.99 BMI), 32 (21.9%) as severe (15-15.99 BMI), and 45 (30.8%) as extreme (<15 BMI). No significant group differences were found for age, CIA and EDE-Q global or subscale scores, frequency of laxative use, self-induced vomiting, binge eating, or excessive exercise. This study found little empirical evidence to support the utility of DSM-5 severity rating scheme to differentiate adults with AN in terms of core eating disorder pathology or associated psychosocial impairment. © 2017 Wiley Periodicals, Inc.

Aerosols and Aerosol-related haze forecasting in China Meteorological Adminstration

NASA Astrophysics Data System (ADS)

Zhou, Chunhong; Zhang, Xiaoye; Gong, Sunling; Liu, Hongli; Xue, Min

2017-04-01

CMA Unified Atmospheric Chemistry Environmental Forecasting System (CUACE) is a unified numerical chemical weather forecasting system with BC, OC, Sulfate, Nitrate, Ammonia, Dust and Sea-Salt aerosols and their sources, gas to particle processes, SOA, microphysics and transformation. With an open interface, CUACE has been online coupled to mesoscale model MM5 and the new NWP system GRAPES (Global/Regional Assimilation and Prediction Enhanced System)min CMA. With Chinese Emissions from Cao and Zhang(2012 and 2013), a forecasting system called CUACE/Haze-fog has been running in real time in CMA and issue 5-days PM10, O3 and Visibility forecasts. A comprehensive ACI scheme has also been developed in CUACE Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The results show that interactive aerosols with the WDM6 in CUACE obviously improve the clouds properties and the precipitation, showing 24% to 48% enhancements of TS scoring for 6-h precipitation .

The site-specific basicity of thyroid hormones and their precursors as regulators of their biological functions.

PubMed

Tóth, Gergo; Hosztafi, Sándor; Kovács, Zsuzsanna; Noszál, Béla

2012-03-05

The complete macro- and microequilibrium analyses of thyroxine, liothyronine, reverse liothyronine and their biological precursors--diiodotyrosine, monoiodotyrosine and tyrosine are presented. Their biosyntheses, receptor- and transport protein-binding are shown to be distinctively dependent on the phenolate basicity. The protonation macroconstants were determined by (1)H NMR-pH and/or UV-pH titrations. Microconstants of the minor microspecies were determined by deductive methods, in which O-methylated and carboxymethylated derivatives were synthesized, and the combination of their NMR-pH and UV-pH titration provided the experimental base to evaluate all the microconstants. NMR-pH profiles, macro-, and microscopic protonation schemes, and species-specific diagrams are included. Biosyntheses of the thyroid hormones take place by oxidative coupling of two iodotyrosine residues catalyzed by thyreoperoxidase in thyreoglobulin. On the grounds of our phenolate microconstants of precursors the thyroxine over liothyronine ratio needs to be 9:1 after their biosynthesis in thyroid gland, which is in good agreement with biochemical data. The microconstants show that the phenolates are in proton donor (-OH) form in liothyronine whereas they occur in proton acceptor (-O(-)) form in thyroxine at the pH of blood. These facts explain several facts that have previously been empirically known: the affinity of liothyronine for the receptor is higher than that of thyroxine, the affinity of thyroxine for the transport proteins is higher than that of liothyronine and the selectivity of thyroxine for the OATP1C1 organic anion transporter is higher than that of liothyronine. Copyright © 2011 Elsevier B.V. All rights reserved.

Comparison of the co-gasification of sewage sludge and food wastes and cost-benefit analysis of gasification- and incineration-based waste treatment schemes.

PubMed

You, Siming; Wang, Wei; Dai, Yanjun; Tong, Yen Wah; Wang, Chi-Hwa

2016-10-01

The compositions of food wastes and their co-gasification producer gas were compared with the existing data of sewage sludge. Results showed that food wastes are more favorable than sewage sludge for co-gasification based on residue generation and energy output. Two decentralized gasification-based schemes were proposed to dispose of the sewage sludge and food wastes in Singapore. Monte Carlo simulation-based cost-benefit analysis was conducted to compare the proposed schemes with the existing incineration-based scheme. It was found that the gasification-based schemes are financially superior to the incineration-based scheme based on the data of net present value (NPV), benefit-cost ratio (BCR), and internal rate of return (IRR). Sensitivity analysis was conducted to suggest effective measures to improve the economics of the schemes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reconstruction based finger-knuckle-print verification with score level adaptive binary fusion.

PubMed

Gao, Guangwei; Zhang, Lei; Yang, Jian; Zhang, Lin; Zhang, David

2013-12-01

Recently, a new biometrics identifier, namely finger knuckle print (FKP), has been proposed for personal authentication with very interesting results. One of the advantages of FKP verification lies in its user friendliness in data collection. However, the user flexibility in positioning fingers also leads to a certain degree of pose variations in the collected query FKP images. The widely used Gabor filtering based competitive coding scheme is sensitive to such variations, resulting in many false rejections. We propose to alleviate this problem by reconstructing the query sample with a dictionary learned from the template samples in the gallery set. The reconstructed FKP image can reduce much the enlarged matching distance caused by finger pose variations; however, both the intra-class and inter-class distances will be reduced. We then propose a score level adaptive binary fusion rule to adaptively fuse the matching distances before and after reconstruction, aiming to reduce the false rejections without increasing much the false acceptances. Experimental results on the benchmark PolyU FKP database show that the proposed method significantly improves the FKP verification accuracy.

Decoding the auditory brain with canonical component analysis.

PubMed

de Cheveigné, Alain; Wong, Daniel D E; Di Liberto, Giovanni M; Hjortkjær, Jens; Slaney, Malcolm; Lalor, Edmund

2018-05-15

The relation between a stimulus and the evoked brain response can shed light on perceptual processes within the brain. Signals derived from this relation can also be harnessed to control external devices for Brain Computer Interface (BCI) applications. While the classic event-related potential (ERP) is appropriate for isolated stimuli, more sophisticated "decoding" strategies are needed to address continuous stimuli such as speech, music or environmental sounds. Here we describe an approach based on Canonical Correlation Analysis (CCA) that finds the optimal transform to apply to both the stimulus and the response to reveal correlations between the two. Compared to prior methods based on forward or backward models for stimulus-response mapping, CCA finds significantly higher correlation scores, thus providing increased sensitivity to relatively small effects, and supports classifier schemes that yield higher classification scores. CCA strips the brain response of variance unrelated to the stimulus, and the stimulus representation of variance that does not affect the response, and thus improves observations of the relation between stimulus and response. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

An efficient and accurate molecular alignment and docking technique using ab initio quality scoring

PubMed Central

Füsti-Molnár, László; Merz, Kenneth M.

2008-01-01

An accurate and efficient molecular alignment technique is presented based on first principle electronic structure calculations. This new scheme maximizes quantum similarity matrices in the relative orientation of the molecules and uses Fourier transform techniques for two purposes. First, building up the numerical representation of true ab initio electronic densities and their Coulomb potentials is accelerated by the previously described Fourier transform Coulomb method. Second, the Fourier convolution technique is applied for accelerating optimizations in the translational coordinates. In order to avoid any interpolation error, the necessary analytical formulas are derived for the transformation of the ab initio wavefunctions in rotational coordinates. The results of our first implementation for a small test set are analyzed in detail and compared with published results of the literature. A new way of refinement of existing shape based alignments is also proposed by using Fourier convolutions of ab initio or other approximate electron densities. This new alignment technique is generally applicable for overlap, Coulomb, kinetic energy, etc., quantum similarity measures and can be extended to a genuine docking solution with ab initio scoring. PMID:18624561

Are health workers motivated by income? Job motivation of Cambodian primary health workers implementing performance-based financing.

PubMed

Khim, Keovathanak

2016-01-01

Financial incentives are widely used in performance-based financing (PBF) schemes, but their contribution to health workers' incomes and job motivation is poorly understood. Cambodia undertook health sector reform from the middle of 2009 and PBF was employed as a part of the reform process. This study examines job motivation for primary health workers (PHWs) under PBF reform in Cambodia and assesses the relationship between job motivation and income. A cross-sectional self-administered survey was conducted on 266 PHWs, from 54 health centers in the 15 districts involved in the reform. The health workers were asked to report all sources of income from public sector jobs and provide answers to 20 items related to job motivation. Factor analysis was conducted to identify the latent variables of job motivation. Factors associated with motivation were identified through multivariable regression. PHWs reported multiple sources of income and an average total income of US$190 per month. Financial incentives under the PBF scheme account for 42% of the average total income. PHWs had an index motivation score of 4.9 (on a scale from one to six), suggesting they had generally high job motivation that was related to a sense of community service, respect, and job benefits. Regression analysis indicated that income and the perception of a fair distribution of incentives were both statistically significant in association with higher job motivation scores. Financial incentives used in the reform formed a significant part of health workers' income and influenced their job motivation. Improving job motivation requires fixing payment mechanisms and increasing the size of incentives. PBF is more likely to succeed when income, training needs, and the desire for a sense of community service are addressed and institutionalized within the health system.

Comparison of Relative Binding Affinities for Trout and Human Estrogen Receptor Based upon Different Competitive Binding Assays

EPA Science Inventory

The development of a predictive model based upon a single aquatic species inevitably raises the question of whether this information is valid for other species. To partially address this question, relative binding affinities (RBA) for six alkylphenols (para-substituted, n- and b...

Applications of the gambling score in evaluating earthquake predictions and forecasts

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Zechar, Jeremy D.; Jiang, Changsheng; Console, Rodolfo; Murru, Maura; Falcone, Giuseppe

2010-05-01

This study presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points bet by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. For discrete predictions, we apply this method to evaluate performance of Shebalin's predictions made by using the Reverse Tracing of Precursors (RTP) algorithm and of the outputs of the predictions from the Annual Consultation Meeting on Earthquake Tendency held by China Earthquake Administration. For the continuous case, we use it to compare the probability forecasts of seismicity in the Abruzzo region before and after the L'aquila earthquake based on the ETAS model and the PPE model.

Modern affinity reagents: Recombinant antibodies and aptamers.

PubMed

Groff, Katherine; Brown, Jeffrey; Clippinger, Amy J

2015-12-01

Affinity reagents are essential tools in both basic and applied research; however, there is a growing concern about the reproducibility of animal-derived monoclonal antibodies. The need for higher quality affinity reagents has prompted the development of methods that provide scientific, economic, and time-saving advantages and do not require the use of animals. This review describes two types of affinity reagents, recombinant antibodies and aptamers, which are non-animal technologies that can replace the use of animal-derived monoclonal antibodies. Recombinant antibodies are protein-based reagents, while aptamers are nucleic-acid-based. In light of the scientific advantages of these technologies, this review also discusses ways to gain momentum in the use of modern affinity reagents, including an update to the 1999 National Academy of Sciences monoclonal antibody production report and federal incentives for recombinant antibody and aptamer efforts. In the long-term, these efforts have the potential to improve the overall quality and decrease the cost of scientific research. Copyright © 2015 Elsevier Inc. All rights reserved.

Lactosylamidine-based affinity purification for cellulolytic enzymes EG I and CBH I from Hypocrea jecorina and their properties.

PubMed

Ogata, Makoto; Kameshima, Yumiko; Hattori, Takeshi; Michishita, Kousuke; Suzuki, Tomohiro; Kawagishi, Hirokazu; Totani, Kazuhide; Hiratake, Jun; Usui, Taichi

2010-12-10

Selective adsorption and separation of β-glucosidase, endo-acting endo-β-(1→4)-glucanase I (EG I), and exo-acting cellobiohydrolase I (CBH I) were achieved by affinity chromatography with β-lactosylamidine as ligand. A crude cellulase preparation from Hypocrea jecorina served as the source of enzyme. When crude cellulase was applied to the lactosylamidine-based affinity column, β-glucosidase appeared in the unbound fraction. By contrast, EG I and CBH I were retained on the column and then separated from each other by appropriately adjusting the elution conditions. The relative affinities of the enzymes, based on their column elution conditions, were strongly dependent on the ligand. The highly purified EG I and CBH I, obtained by affinity chromatography, were further purified by Mono P and DEAE chromatography, respectively. EG I and CBH I cleave only at the phenolic bond in p-nitrophenyl glycosides with lactose and N-acetyllactosamine (LacNAc). By contrast, both scissile bonds in p-nitrophenyl glycosides with cellobiose were subject to hydrolysis although with important differences in their kinetic parameters. Copyright © 2010 Elsevier Ltd. All rights reserved.

Design of Bcl-2 and Bcl-xL Inhibitors with Subnanomolar Binding Affinities Based upon a New Scaffold

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Haibin; Chen, Jianfang; Meagher, Jennifer L.

Employing a structure-based strategy, we have designed a new class of potent small-molecule inhibitors of the anti-apoptotic proteins Bcl-2 and Bcl-xL. An initial lead compound with a new scaffold was designed based upon the crystal structure of Bcl-xL and U.S. Food and Drug Administration (FDA) approved drugs and was found to have an affinity of 100 {micro}M for both Bcl-2 and Bcl-xL. Linking this weak lead to another weak-affinity fragment derived from Abbott's ABT-737 led to an improvement of the binding affinity by a factor of >10,000. Further optimization ultimately yielded compounds with subnanomolar binding affinities for both Bcl-2 andmore » Bcl-xL and potent cellular activity. The best compound (21) binds to Bcl-xL and Bcl-2 with K{sub i} < 1 nM, inhibits cell growth in the H146 and H1417 small-cell lung cancer cell lines with IC{sub 50} values of 60-90 nM, and induces robust cell death in the H146 cancer cell line at 30-100 nM.« less

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands.

PubMed

Saleh, Noureldin; Ibrahim, Passainte; Saladino, Giorgio; Gervasio, Francesco Luigi; Clark, Timothy

2017-05-22

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol -1 ). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

A Comprehensive Histological Assessment of Osteoarthritis Lesions in Mice

PubMed Central

McNulty, Margaret A.; Loeser, Richard F.; Davey, Cynthia; Callahan, Michael F.; Ferguson, Cristin M.; Carlson, Cathy S.

2011-01-01

Objective: Accurate histological assessment of osteoarthritis (OA) is critical in studies evaluating the effects of interventions on disease severity. The purpose of the present study was to develop a histological grading scheme that comprehensively and quantitatively assesses changes in multiple tissues that are associated with OA of the stifle joint in mice. Design: Two representative midcoronal sections from 158 stifle joints, including naturally occurring and surgically induced OA, were stained with H&E and Safranin-O stains. All slides were evaluated to characterize the changes present. A grading scheme that includes both measurements and semiquantitative scores was developed, and principal components analysis (PCA) was applied to the resulting data from the medial tibial plateaus. A subset of 30 tibial plateaus representing a wide range of severity was then evaluated by 4 observers. Reliability of the results was evaluated using intraclass correlation coefficients (ICCs) and area under the receiver operating characteristic (ROC) curve. Results: Five factors were retained by PCA, accounting for 74% of the total variance. Interobserver and intraobserver reproducibilities for evaluations of articular cartilage and subchondral bone were acceptable. The articular cartilage integrity and chondrocyte viability factor scores were able to distinguish severe OA from normal, minimal, mild, and moderate disease. Conclusion: This newly developed grading scheme and resulting factors characterize a range of joint changes in mouse stifle joints that are associated with OA. Overall, the newly developed scheme is reliable and reproducible, characterizes changes in multiple tissues, and provides comprehensive information regarding a specific site in the stifle joint. PMID:26069594

The UKNEQAS scheme for cerebrospinal fluid haem pigments: a paradigm for service improvement.

PubMed

Beetham, Robert; Egner, William; Patel, Dina

2011-11-01

We describe the programme of an established External Quality Assurance (EQA) provider and a Specialist Advisory Group (SAG) to develop a successful EQA scheme for cerebrospinal fluid (CSF) haem pigments as an example of a professionally led, unfunded initiative with the real potential to benefit patients. Within three years, we had assured sample stability, stoichiometry, and published best practice guidelines, enabling both analytical results and interpretation to be assessed and reported with an educative summary of the desired responses. Misclassification scoring of analysis and interpretation was introduced. Following audit, guidelines were modified and republished. The outcomes were as follows: Participant numbers increased from 63 at inception to 150 10 years later; The percentage of participants using visual inspection, a poor practice indicator, decreased from 27% to less than 1%; In all, 94-100% of participants consistently detected minor increases in bilirubin over the last four years of the scheme; More than 93% of participants were able to interpret analytical results linked to straightforward clinical scenarios; Misclassification scoring demonstrated that more complex scenarios repeatedly posed problems and is the next challenge to address. Scheme success is attributed to the experience of the operator and the formation of a voluntary expert advisory group, with both concerned to advance science and patient safety and thus contribute unpaid time and effort in order to succeed. In times of fiscal constraint, such resource may not be so readily available, yet is a vital part of continuous quality improvement for the benefit of patients.

Correlations of diffusion tensor imaging values and symptom scores in patients with schizophrenia.

PubMed

Michael, Andrew M; Calhoun, Vince D; Pearlson, Godfrey D; Baum, Stefi A; Caprihan, Arvind

2008-01-01

Abnormalities in white matter (WM) brain regions are attributed as a possible biomarker for schizophrenia (SZ). Diffusion tensor imaging (DTI) is used to capture WM tracts. Psychometric tests that evaluate the severity of symptoms of SZ are clinically used in the diagnosis process. In this study we investigate the correlates of scalar DTI measures, such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity with behavioral test scores. The correlations were found by different schemes: mean correlation with WM atlas regions and multiple regression of DTI values with test scores. The corpus callosum, superior longitudinal fasciculus right and inferior longitudinal fasciculus left were found to be having high correlations with test scores.

FAST TRACK COMMUNICATION: Affine constellations without mutually unbiased counterparts

NASA Astrophysics Data System (ADS)

Weigert, Stefan; Durt, Thomas

2010-10-01

It has been conjectured that a complete set of mutually unbiased bases in a space of dimension d exists if and only if there is an affine plane of order d. We introduce affine constellations and compare their existence properties with those of mutually unbiased constellations. The observed discrepancies make a deeper relation between the two existence problems unlikely.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Fluorogen-Activating-Proteins as Universal Affinity Biosensors for Immunodetection

PubMed Central

Gallo, Eugenio; Vasilev, Kalin V.; Jarvik, Jonathan

2014-01-01

Fluorogen-activating-proteins (FAPs) are a novel platform of fluorescence biosensors utilized for protein discovery. The technology currently demands molecular manipulation methods that limit its application and adaptability. Here, we highlight an alternative approach based on universal affinity reagents for protein detection. The affinity reagents were engineered as bi-partite fusion proteins, where the specificity moiety is derived from IgG-binding proteins –Protein-A or Protein-G – and the signaling element is a FAP. In this manner, primary antibodies provide the antigenic selectivity against a desired protein in biological samples, while FAP affinity reagents target the constant region (Fc) of antibodies and provide the biosensor component of detection. Fluorescence results using various techniques indicate minimal background and high target specificity for exogenous and endogenous proteins in mammalian cells. Additionally, FAP-based affinity reagents provide enhanced properties of detection previously absent using conventional affinity systems. Distinct features explored in this report include: (1) unfixed signal wavelengths (excitation and emission) determined by the particular fluorogen chosen, (2) real-time user controlled fluorescence on-set and off-set, (3) signal wavelength substitution while performing live analysis, and (4) enhanced resistance to photobleaching. PMID:24122476

PMD compensation in multilevel coded-modulation schemes with coherent detection using BLAST algorithm and iterative polarization cancellation.

PubMed

Djordjevic, Ivan B; Xu, Lei; Wang, Ting

2008-09-15

We present two PMD compensation schemes suitable for use in multilevel (M>or=2) block-coded modulation schemes with coherent detection. The first scheme is based on a BLAST-type polarization-interference cancellation scheme, and the second scheme is based on iterative polarization cancellation. Both schemes use the LDPC codes as channel codes. The proposed PMD compensations schemes are evaluated by employing coded-OFDM and coherent detection. When used in combination with girth-10 LDPC codes those schemes outperform polarization-time coding based OFDM by 1 dB at BER of 10(-9), and provide two times higher spectral efficiency. The proposed schemes perform comparable and are able to compensate even 1200 ps of differential group delay with negligible penalty.

Can a totally different approach to soft tissue computer aided detection (CADe) result in affecting radiologists' decisions?

NASA Astrophysics Data System (ADS)

Gur, David

2018-03-01

We tested whether a case based CADe scheme, developed only on negatively interpreted screening mammograms, has predictive value for cancer detection during subsequent screening and how this approach may affect radiologists' performances when alerting them to a small subset ( 15%) of exams on which radiologists tend to miss cancers. A series of six parameters case based CADe schemes, using 200 negative mammograms (800 images 100 women with breast cancer at subsequent screening and 100 women who remained negative), carefully matched by age and breast density, were optimized. CADe alone schemes performed at AUC=0.68 (+/- 0.01). Five radiologists and 4 residents interpreted the same cases and performed at AUC =0.71 (experienced radiologists) and AUC= 0.61 (residents). With the "CADe warnings" shown to the interpreters only if they did not recall one of 24 highest CADe scoring cases, assisted performance of radiologists and residents respectively, were 0.71 and 0.63 (p>0.05). However, when the CADe alone performance was raised to an AUC=0.78, by artificially increasing the number of possible warnings from 16 to 24, radiologists' performances significantly improved from an AUC of 0.68 to 0.72 (p<0.05). In conclusion, the use case based information other than breast density could highlight a small fraction of women whose cancers are more likely to be missed by radiologists and later detected during subsequent mammograms, thereby, leading to an assisted approach that improves radiologists' performances. However, to be effective, the performance of the CADe alone should be substantially higher (e.g. ΔAUC >=0.07) than that of the un-assisted radiologist.

Rationale for the new GP deprivation payment scheme in England: effects of moving from electoral ward to enumeration district underprivileged area scores.

PubMed Central

Bajekal, M; Alves, B; Jarman, B; Hurwitz, B

2001-01-01

BACKGROUND: The Department of Health introduced a new deprivation payments system for general practitioners (GPs) on 1 April 1999. Following a three-year phasing-in process, registered patients will attract deprivation payments based on the underprivileged area (UPA) score of their enumeration district (ED) of residence, rather than their electoral ward, changing the pattern and distribution of payments throughout England. AIM: To assess the rationale behind the changed deprivation payments system for GPs in England and to examine its impact on GP and practice payments. DESIGN OF STUDY: A quantitative study modelling practice-based deprivation payments. SETTING: A total of 25,450 unrestricted principal GPs in 8919 practices in England. METHOD: The effect of three new components in the system were examined: changes in the ED score ranges attracting payment, the percentage increase in the size of successive payment bands, and the total budget. The relationship between consultation rates (used as a proxy for workload) and UPA score was examined, together with changes in GP payments calculated nationally and by geographical area. RESULTS: A total of 11.6% of the population of England live in wards with a UPA score of 30 or more, qualifying for deprivation payments, and a similar proportion (11.4%) live in EDs with a UPA score of 20 or more. The larger percentage increases in the size of payments in successive ED UPA bands is supported by the modelled relationship between consultation rate and UPA score. Financially, under the new deprivations payment system, entitlement widens with 88% of practices receiving a payment. Overall, 74% of GPs gain and 13% lose (3% losing more than 1500 Pounds), with 13% receiving no payment. CONCLUSION: The new ED system maps onto the previous system well. Moreover, it more finely discriminates between smaller areas of different relative deprivation and, thereby, targets payments more accurately. PMID:11407049

Rationale for the new GP deprivation payment scheme in England: effects of moving from electoral ward to enumeration district underprivileged area scores.

PubMed

Bajekal, M; Alves, B; Jarman, B; Hurwitz, B

2001-06-01

The Department of Health introduced a new deprivation payments system for general practitioners (GPs) on 1 April 1999. Following a three-year phasing-in process, registered patients will attract deprivation payments based on the underprivileged area (UPA) score of their enumeration district (ED) of residence, rather than their electoral ward, changing the pattern and distribution of payments throughout England. To assess the rationale behind the changed deprivation payments system for GPs in England and to examine its impact on GP and practice payments. A quantitative study modelling practice-based deprivation payments. A total of 25,450 unrestricted principal GPs in 8919 practices in England. The effect of three new components in the system were examined: changes in the ED score ranges attracting payment, the percentage increase in the size of successive payment bands, and the total budget. The relationship between consultation rates (used as a proxy for workload) and UPA score was examined, together with changes in GP payments calculated nationally and by geographical area. A total of 11.6% of the population of England live in wards with a UPA score of 30 or more, qualifying for deprivation payments, and a similar proportion (11.4%) live in EDs with a UPA score of 20 or more. The larger percentage increases in the size of payments in successive ED UPA bands is supported by the modelled relationship between consultation rate and UPA score. Financially, under the new deprivations payment system, entitlement widens with 88% of practices receiving a payment. Overall, 74% of GPs gain and 13% lose (3% losing more than 1500 Pounds), with 13% receiving no payment. The new ED system maps onto the previous system well. Moreover, it more finely discriminates between smaller areas of different relative deprivation and, thereby, targets payments more accurately.

Engineering of Bispecific Affinity Proteins with High Affinity for ERBB2 and Adaptable Binding to Albumin

PubMed Central

Nilvebrant, Johan; Åstrand, Mikael; Georgieva-Kotseva, Maria; Björnmalm, Mattias; Löfblom, John; Hober, Sophia

2014-01-01

The epidermal growth factor receptor 2, ERBB2, is a well-validated target for cancer diagnostics and therapy. Recent studies suggest that the over-expression of this receptor in various cancers might also be exploited for antibody-based payload delivery, e.g. antibody drug conjugates. In such strategies, the full-length antibody format is probably not required for therapeutic effect and smaller tumor-specific affinity proteins might be an alternative. However, small proteins and peptides generally suffer from fast excretion through the kidneys, and thereby require frequent administration in order to maintain a therapeutic concentration. In an attempt aimed at combining ERBB2-targeting with antibody-like pharmacokinetic properties in a small protein format, we have engineered bispecific ERBB2-binding proteins that are based on a small albumin-binding domain. Phage display selection against ERBB2 was used for identification of a lead candidate, followed by affinity maturation using second-generation libraries. Cell surface display and flow-cytometric sorting allowed stringent selection of top candidates from pools pre-enriched by phage display. Several affinity-matured molecules were shown to bind human ERBB2 with sub-nanomolar affinity while retaining the interaction with human serum albumin. Moreover, parallel selections against ERBB2 in the presence of human serum albumin identified several amino acid substitutions that dramatically modulate the albumin affinity, which could provide a convenient means to control the pharmacokinetics. The new affinity proteins competed for ERBB2-binding with the monoclonal antibody trastuzumab and recognized the native receptor on a human cancer cell line. Hence, high affinity tumor targeting and tunable albumin binding were combined in one small adaptable protein. PMID:25089830

DNA sequence determinants controlling affinity, stability and shape of DNA complexes bound by the nucleoid protein Fis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hancock, Stephen P.; Stella, Stefano; Cascio, Duilio

The abundant Fis nucleoid protein selectively binds poorly related DNA sequences with high affinities to regulate diverse DNA reactions. Fis binds DNA primarily through DNA backbone contacts and selects target sites by reading conformational properties of DNA sequences, most prominently intrinsic minor groove widths. High-affinity binding requires Fis-stabilized DNA conformational changes that vary depending on DNA sequence. In order to better understand the molecular basis for high affinity site recognition, we analyzed the effects of DNA sequence within and flanking the core Fis binding site on binding affinity and DNA structure. X-ray crystal structures of Fis-DNA complexes containing variable sequencesmore » in the noncontacted center of the binding site or variations within the major groove interfaces show that the DNA can adapt to the Fis dimer surface asymmetrically. We show that the presence and position of pyrimidine-purine base steps within the major groove interfaces affect both local DNA bending and minor groove compression to modulate affinities and lifetimes of Fis-DNA complexes. Sequences flanking the core binding site also modulate complex affinities, lifetimes, and the degree of local and global Fis-induced DNA bending. In particular, a G immediately upstream of the 15 bp core sequence inhibits binding and bending, and A-tracts within the flanking base pairs increase both complex lifetimes and global DNA curvatures. Taken together, our observations support a revised DNA motif specifying high-affinity Fis binding and highlight the range of conformations that Fis-bound DNA can adopt. Lastly, the affinities and DNA conformations of individual Fis-DNA complexes are likely to be tailored to their context-specific biological functions.« less