bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic alignment detects remote homology in a pair of protein sequences without homologous sequence information
Authors: Koike Ryotaro , Kinoshita Kengo , Kidera Akinori 
Published: December 2006

AbstractDynamic programming (DP) and its heuristic algorithms are the most fundamental methods for similarity searches of amino acid sequences. Their detection power has been improved by including supplemental information, such as homologous sequences in the profile method. Here, we describe a method, probabilistic alignment (PA), that gives improved detection power, but similarly to the original DP, uses only a pair of amino acid sequences. Receiver operating characteristic (ROC) analysis demonstrated that the PA method is far superior to BLAST, and that its sensitivity and selectivity approach to those of PSI‐BLAST. Particularly for orphan proteins having few homologues in the database, PA exhibits much better performance than PSI‐BLAST. On the basis of this observation, we applied the PA method to a homology search of two orphan proteins, Latexin and Resuscitation‐promoting factor domain. Their molecular functions have been described based on structural similarities, but sequence homologues have not been identified by PSI‐BLAST. PA successfully detected sequence homologues for the two proteins and confirmed that the observed structural similarities are the result of an evolutional relationship. Proteins 2007. © 2006 Wiley‐Liss, Inc.
Prediction‐based fingerprints of protein–protein interactions
Authors: Porollo Aleksey , Meller Jarosław 
Published: December 2006

AbstractThe recognition of protein interaction sites is an important intermediate step toward identification of functionally relevant residues and understanding protein function, facilitating experimental efforts in that regard. Toward that goal, the authors propose a novel representation for the recognition of protein–protein interaction sites that integrates enhanced relative solvent accessibility (RSA) predictions with high resolution structural data. An observation that RSA predictions are biased toward the level of surface exposure consistent with protein complexes led the authors to investigate the difference between the predicted and actual (i.e., observed in an unbound structure) RSA of an amino acid residue as a fingerprint of interaction sites. The authors demonstrate that RSA prediction‐based fingerprints of protein interactions significantly improve the discrimination between interacting and noninteracting sites, compared with evolutionary conservation, physicochemical characteristics, structure‐derived and other features considered before. On the basis of these observations, the authors developed a new method for the prediction of protein–protein interaction sites, using machine learning approaches to combine the most informative features into the final predictor. For training and validation, the authors used several large sets of protein complexes and derived from them nonredundant representative chains, with interaction sites mapped from multiple complexes. Alternative machine learning techniques are used, including Support Vector Machines and Neural Networks, so as to evaluate the relative effects of the choice of a representation and a specific learning algorithm. The effects of induced fit and uncertainty of the negative (noninteracting) class assignment are also evaluated. Several representative methods from the literature are reimplemented to enable direct comparison of the results. Using rigorous validation protocols, the authors estimated that the new method yields the overall classification accuracy of about 74% and Matthews correlation coefficients of 0.42, as opposed to up to 70% classification accuracy and up to 0.3 Matthews correlation coefficient for methods that do not utilize RSA prediction‐based fingerprints. The new method is available at http://sppider.cchmc.org. Proteins 2007. © 2006 Wiley‐Liss, Inc.
Data Pipelines and Virtual Screening: Automating the Process
Authors: Brown Robert D. , Varma‐O'Brien Shikha , Rogers David 
Published: December 2006

AbstractThe application of virtual screens to sets of ligands can involve several complex modeling and database packages and a considerable amount of manual intervention to transfer and reformat data between computational steps. This is time‐consuming and error‐prone for a computational chemist, and can put the process beyond the capabilities of a project scientist. In this paper, we discuss the application of a workflow methodology known as data pipelining to automate the process of virtual screening. We show that this can allow computational chemists to automate the application of virtual screens, encapsulate their expertise in the form of computational protocols (workflows), and deploy these protocols to bench scientists to allow them to apply virtual screening methods in a simple, automated fashion.
Estimation of Compartmental Half‐lives of Organic Compounds – Structural Similarity versus EPI‐Suite
Authors: Kühne Ralph , Ebert Ralf‐Uwe , Schüürmann Gerrit 
Published: December 2006

AbstractA k Nearest Neighbors (KNN) approach is developed to extrapolate from existing semiquantitative compartmental half‐lives of organic compounds to respective data for untested substances. It is based on the evaluation of structural similarity through atom‐centered fragments (ACFs). For the model development and leave‐one‐out cross‐validation, a set of 293 compounds with reference half‐lives for the four compartments air, water, soil, and sediment was taken from literature. Comparative analysis of the model performance with results based on EPI‐Suite predictions of degradation rates due to indirect photolysis, biodegradation, and hydrolysis demonstrates the superiority of the new approach to predict compartmental half‐lives. The latter are needed as input information for modeling the multimedia fate and life‐time of organic compounds. The discussion includes an analysis of the problems associated with converting process‐specific loss rates into compartmental half‐lives.
Atom‐Based 2D Quadratic Indices in Drug Discovery of Novel Tyrosinase Inhibitors: Results of In Silico Studies Supported by Experimental Results
Authors: Ponce Yovani Marrero , Khan Mahmud Tareq Hassan , Martín Gerardo M. Casañola , Ather Arjumand , Sultankhodzhaev Mukhlis N. , Torrens Francisco , Rotondo Richard , Alvarado Ysaias J. 
Published: December 2006

AbstractHerein we present results of QSAR studies of tyrosinase inhibitors employing one of the atom‐based TOMOCOMD‐CARDD (acronym of TOpological MOlecular COMputer Design‐Computer Aided “Rational” Drug Design) descriptors, molecular quadratic indices, and Linear Discriminant Analysis (LDA) as pattern recognition method. In this way, a database of 246 organic chemicals, reported as tyrosinase inhibitors having great structural variability, was analyzed and presented as a helpful tool, not only for theoretical chemists but also for other researchers in this area. In total, 12 LDA‐based QSAR models were obtained, the first six with the non‐stochastic total and local quadratic indices and the six remaining models with the stochastic molecular descriptors. The best two models for the non‐stochastic and stochastic molecular descriptors, showed an appropriate overall accuracy (92.68 and 89.10%, respectively) and a high Matthews correlation coefficient (C of 0.85 and of 0.84, correspondingly) when applied to the training set. External validation series were also used to validate the obtained models; the 91.67% (C=0.82) and 90.00% (C=0.78), were correctly classified, respectively. In order to show the possibilities of the present approach for the ligand‐based virtual screening of tyrosinase inhibitors, the developed models were used afterwards in a simulation of a virtual search for tyrosinase inhibitors. For instance, more than 93% (93.33%) and 96% (96.66%) of the screened chemicals were correctly classified by the two best LDA‐based QSAR models developed with non‐stochastic and stochastic quadratic indices, respectively. Finally, the combination of the obtained models permitted the selection/identification of new diterpenoidal alkaloid leads as tyrosinase inhibitors. The found activity is supported by observed inhibitory effects on mushroom tyrosinase enzyme, even comparable with some reference tyrosinase inhibitors. These results support a role for TOMOCOMD‐CARDD descriptors in the biosilico discovery of novel tyrosinase inhibitors from large databases of chemical structures (virtual or “in silico”), which may be used to prevent or treat pigmentation disorders.
Principal Component Analysis of Catalytic Functions in the Composition Space of Heterogeneous Catalysts
Authors: Sieg Simone C. , Suh Changwon , Schmidt Timm , Stukowski Michael , Rajan Krishna , Maier Wilhelm F. 
Published: December 2006

AbstractThe objective of this paper is to identify which combinations of constituents of heterogeneous catalysts are related to which final products from a large combinatorially generated dataset. To this end, data on the composition of catalysts are combined with a set of four catalytic activities, and analyzed using a Principle Component Analysis (PCA). From the first attempt of PCA, a dataset of pentanary‐mixed metal oxides, CraMobNicCodMneOx, is visualized on the planes of principal components (PCs) in a way of linking the composition spread with the activities toward each product. It has been possible to identify three key elements (Mo, Co, and Cr) out of five by PCA. Having these key elements identified from PCA, a ternary system of mixed metal oxide catalysts, MoaCobCrcOx, was analyzed again in the PC space for further relationships between composition of catalysts and activities of final products. These two case studies demonstrate how large multidimensional datasets can be analyzed to identify relevant key parameters for catalyst discovery and optimization.
Quantitative Cationic Activity Relationships for Predicting Toxicity of Metal Ions from Physicochemical Properties and Natural Occurrence Levels
Authors: Walker John D. , Enache Monica , Dearden John C. 
Published: December 2006

AbstractQuantitative Cationic Activity Relationships (QCARs) were developed to predict the toxicity of metal ions from physicochemical properties and natural occurrence levels. In vivo toxicity data for different concentrations of nitrate salts of 17 metal ions were developed based on germination of sunflower seeds (F.1. Helianthus annuus ‘Sunspot’) in distilled water. The EC50 data were reported as the concentration giving 50% inhibition of radicle growth 1 day after emergence. Stepwise regression of the toxicity data produced correlations with some physicochemical properties and natural occurrence levels. For physicochemical properties, good results were obtained with the density of the elements, enthalpy of formation of metal sulphides and the stability constants of metal ions with sulphate ($\rm{ r_{{\rm{adj}}.}^2 }$=0.72−0.81). For natural occurrence levels, good results were obtained with metal concentrations in soil, the median elemental composition of soils and the calculated mean of the elemental content in land plants ($\rm{ r_{{\rm{adj}}.}^2 }$=0.69−0.83).
3‐D‐QSAR Analysis of 2‐(Oxalylamino) benzoic acid Class of Protein Tyrosine Phosphatase 1B Inhibitors by CoMFA and Cerius2.GA
Authors: Ramar Subbiah , Bag Seema , Tawari Nilesh R. , Degani Mariam S. 
Published: December 2006

AbstractThree‐Dimensional Quantitative Structure–Activity Relationship (3‐D‐QSAR) studies for 2‐(oxalylamino) benzoic acids as Protein Tyrosine Phosphatase 1B (PTP1B) inhibitors were performed using the genetic function approximation algorithm (Cerius2.GA) and Comparative Molecular Field Analysis (CoMFA). A five‐term equation was developed with crossvalidated $\rm{ r_{}^{\rm{2}} }$ ($\rm{ r_{{\rm{CV}}}^{\rm{2}} }$) and conventional correlation coefficient (r2) of 0.642 and 0.748, respectively, using Cerius2.GA. The CoMFA model from multifit alignment produced good statistical significance with $\rm{ r_{{\rm{CV}}}^{\rm{2}} }$ and r2 of 0.671 and 0.900, respectively. The predictive abilities of Cerius2.GA and CoMFA were determined using a test set of ten molecules giving predictive correlation coefficients of 0.666 and 0.643, respectively, indicating good predictive power. Furthermore, the robustness of the models was verified by bootstrapping analysis. Based on the information derived from Cerius2.GA and CoMFA, we have identified some key features that may be used to design new derivatives and predict their PTP affinities prior to synthesis.
Determination of bond dissociation energies using mass spectrometry
Authors: El‐Nakat John Hanna , Ghanem Noha , Yammine Paolo , Willett Gary , Fisher Keith 
Published: December 2006

AbstractFourier transform ion cyclotron resonance mass spectrometry (FT‐ICR/MS) offers the opportunity for gas phase cluster formation reactions at very low pressures and at temperatures that are different from room temperature. Reactions take place with single positive‐charge metal ions that are normally +2, +3, +4, etc., charged in solution. The ions formed are detected by measuring the current induced by their cyclotron rotation, but they cannot be physically separated and collected. Collision‐induced dissociation (CID) is widely used for ion‐structure determination via the fragmentation of the excited ions. CID study aims to determine the relationship between the Vpp [peak‐to‐peak voltage of the radiofrequency (rf) pulse] and the mass‐to‐charge (m/z) ratio, which will be used for the calculation of the center‐of‐mass translational kinetic energy (Ekcm) of the excited ion under investigation. CID studies are restricted to stable ions with relatively high abundance. Nevertheless, with the evolution of computational chemistry, such problems can be overcome whereby CID calculations will be used to provide the substantial parameters for computer software, such as the Gaussian 03 program, for the structure determination of the less stable NixS anions. The latter constitutes the core for our current research. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007
Sample size determination for logistic regression revisited
Authors: Demidenko Eugene 
Published: December 2006

AbstractThere is no consensus on the approach to compute the power and sample size with logistic regression. Some authors use the likelihood ratio test; some use the test on proportions; some suggest various approximations to handle the multivariate case. We advocate the use of the Wald test since the Z‐score is routinely used for statistical significance testing of regression coefficients. The null‐variance formula became popular from early studies, which contradicts modern software, which utilizes the method of maximum likelihood estimation (MLE), when the variance of the MLE is estimated at the MLE, not at the null. We derive general Wald‐based power and sample size formulas for logistic regression and then apply them to binary exposure and confounder to obtain a closed‐form expression. These formulas are applied to minimize the total sample size in a case–control study to achieve a given power by optimizing the ratio of controls to cases. Approximately, the optimal number of controls to cases is equal to the square root of the alternative odds ratio. Our sample size and power calculations can be carried out online at www.dartmouth.edu/∼eugened. Copyright © 2006 John Wiley & Sons, Ltd.
Methods for the statistical analysis of binary data in split‐mouth designs with baseline measurements
Authors: Donner A. , Zou G. Y. 
Published: December 2006

AbstractMany split‐mouth trials are characterized by the pairing of site‐specific outcome and baseline data within each segment of a subject's mouth. However when the response variable of interest is binary, methods of statistical analysis for this design are not well developed. In this paper we present several analytic approaches that may be taken to the resulting data, showing how the efficiency of statistical inferences can be improved by appropriately incorporating the baseline information. The advantages and disadvantages of the different approaches are discussed in the context of an example from the published literature. The results from a limited simulation study are also presented. Copyright © 2006 John Wiley & Sons, Ltd.
Intervention on occupational stress among teachers in the middle schools in China
Authors: Wu Siying , Li Jian , Wang Mianzhen , Wang Zhiming , Li Huangyuan 
Published: December 2006

AbstractThe purpose of this study was to evaluate the effectiveness of the interventions on occupational stress among teachers in middle schools. The study group consists of 459 teachers (247 men and 212 women) from four middle schools. The control group consists of 502 teachers (271 men and 231 women). The three dimensions of occupational adjustment (including occupational stress, psychological strain, and coping resources) were measured with the Occupational Stress Inventory‐Revised Edition (OSI‐R) and the work ability was assessed with the Work Ability Index (WAI) among teachers. The integrated interventions (involving organizational and individual level intervention) were taken to the teachers in the study group. The main results were as follows. The scores of some scales of occupational role questionnaire and personal strain questionnaire decreased significantly and the scores of some scales of personal resources questionnaire and WAI increased significantly after intervening. This study suggested that interventions were efficient in reducing the teachers' occupational stressors, increased their coping resources and improved their work ability. Copyright © 2006 John Wiley & Sons, Ltd.
Post‐traumatic reactions among rescue personnel before and after exposure to trauma: a brief report
Authors: Ben‐Ezra Menachem , Essar Nir , Saar Ronen 
Published: December 2006

AbstractThere are only a few studies that check rescue personnel before and after exposure to trauma. Peritraumatic dissociation and post‐traumatic reactions were examined among rescue personnel in a rescue course and 36–48h after exposure to a gas pipe explosion in Tel Aviv. The entire rescue personnel were examined for peritraumatic dissociation and post‐traumatic reactions. Only those with prior measurements of peritraumatic dissociation and post‐traumatic reactions were eligible for analysis. The results showed that the only significant increase among rescue personnel was in peritraumatic dissociation between before in comparison to after exposure to trauma. No significant change was found in avoidance, intrusion, and post‐traumatic symptoms. These results correspond with previous studies that found increased peritraumatic dissociation among rescue personnel as a function of exposure severity. Explanations for these results are discussed. Copyright © 2006 John Wiley & Sons, Ltd.
PTSD and ADHD: underlying factors in many cases of burnout
Authors: Brattberg Gunilla 
Published: December 2006

AbstractObjective: To analyse the extent to which traumatic life events, post‐traumatic stress disorder (PTSD) and the neuropsychiatric disorder attention deficit hyperactivity disorder (ADHD) can be contributors associated with burnout and the long‐term sick leave that results from it.Subjects: Sixty‐two individuals on long‐term sick leave due to stress‐related poor health and burnout, and 83 working individuals were screened for the presence of traumatic life events, PTSD and ADHD. Potential background factors involved in burnout were analysed using a multiple logistic regression.Results: Fifty‐two per cent of those on long‐term sick leave were judged to have PTSD and 24 per cent to have ADHD. The number of suspected/possible cases was even higher—71 per cent and 56 per cent, respectively. Nineteen per cent were judged to have both PTSD and ADHD; 56 per cent were judged to have PTSD and/or ADHD. PTSD, ADHD and traumatic life events in the form of sexual assault and severe human suffering were all strongly associated with both burnout and long‐term sick leave.Conclusions: Since ADHD is almost never discussed and PTSD rarely so in the occupational rehabilitation of individuals with burnout, these results should act as a warning signal. Further studies are needed, however, including clinical examinations in order to establish with certainty if PTSD and ADHD can predict burnout followed by long‐term sick leave. Copyright © 2006 John Wiley & Sons, Ltd.
Application of a ray theory model to the prediction of noise emissions from isolated wind turbines and wind parks
Authors: Prospathopoulos John M. , Voutsinas Spyros G. 
Published: December 2006

AbstractVarious propagation models have been developed to estimate the level of noise near residential areas. Predictions and measurements have proven that proper modelling of the propagation medium is of particular importance. In the present work, calculations are performed using a ray theory methodology. The ray trajectory and transport equations are derived from the linear acoustics equations for a moving medium in three dimensions. Ground and atmospheric absorption, wave refraction and diffraction and atmospheric turbulence are taken into account by introducing appropriate coefficients in the equations. In the case of a wind turbine (W/T) it is assumed that noise is produced by a point source located at the rotor centre. Given the sound power spectrum, the noise spectrum at the receiver is obtained by solving the axisymmetric propagation problem. The procedure consists of (a) finding the eigenrays, (b) calculating the energy losses along the eigenrays and (c) synthesizing the sound pressure level (SPL) by superposing the contributions of the eigenrays. In the case of a wind park the total SPL is calculated by superposing the contributions of all W/Ts. Application is made to five cases of isolated W/Ts in terrains of varying complexity. In flat or even smooth terrain the predictions agree well with the measurements. In complex terrain the predictions can be considered satisfactory, taking into account the assumption of constant wind velocity profile. Application to a wind park shows clearly the influence of the terrain on the wind velocity and consequently on the SPL. Copyright © 2006 John Wiley &Sons, Ltd.