bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toward a compact description of molecular electron densities
Authors: Chodkiewicz Michał L. , Howard Siân T. , Woźniak Krzysztof 
Published: March 2004

AbstractA formalism is presented for the description of the electron density in a molecule or its fragment, using only a small number of parameters. The method is based on statistical analysis of a set of fragment electron densities obtained for a given quantum mechanical subsystem embedded in different environments (e.g., substituent groups, external fields). The electron density is expressed as the sum of its average value in such a subsystem and a linear combination of orthonormal functions expressed on a molecular orbital basis and chosen in such a way that each successive function maximally reduces the residual density. The technique used is functional principal component analysis (FPCA), which seems well suited to the statistical properties of the electron density. In addition to providing an efficient means of parameterizing an electron density, the FPCA also appears to provide the basis of a scheme for systematic analysis of the perturbations in electron density caused by changes of the molecular environment. An example of the application of this method, to the aldehyde fragment of HCOX compounds, is presented. Most of the variation of electron density in this fragment (97%) is described by only four functions. The coefficients of the first function correlate (−0.93) with the resonance substituent constants, and the second one with the induction parameterF(−0.9). This approach appears to have many potential applications: in developing rapid density functional methods for large molecules, in more efficient parameterizations of reconstructed experimental densities (from scattering experiments), and in analyzing substituent effects. © 2004 Wiley Periodicals, Inc. Int J Quantum Chem, 2004
Rotavirus typing methods and algorithms
Authors: Fischer Thea K. , Gentsch Jon R. 
Published: March 2004

AbstractVaccination is the current strategy for control and prevention of severe rotavirus infections, a major cause of acute, dehydrating diarrhoea in young children worldwide. Public health interventions aimed at improving water, food and sanitation are unlikely adequately to control the disease. The development of vaccines against severe rotavirus diarrhoea is based upon homotypic or heterotypic protection provided against either a single common G serotype (monovalent vaccines) or against multiple serotypes (multivalent vaccines). Rotavirus strain surveillance has a high priority in disease control programmes worldwide. The continued identification of the most common G and P serotypes for inclusion in vaccines is an important priority. And subsequent to the introduction of a vaccine candidate, not only monitoring of circulating strains is recommended, but also surveillance of potential reassortment of animal rotavirus genes from the vaccine into human rotavirus strains is critical. Conventional methods used in the characterisation of rotavirus strains, such as enzyme immunoassay serotyping and reverse‐transcription PCR‐based genotyping often fail to identify uncommon and newly appearing strains. The application of newer molecular approaches, including sequencing and oligonucleotide microarray hybridisation, may be required to characterise such strains. The present paper presents a brief overview of the variety of standard methods available, followed by suggestions for a systematic approach for routine rotavirus strain surveillance as well as for characterisation of incompletely typed rotavirus strains. Improved detection and characterisation of incompletely typed strains will help to develop a comprehensive strain surveillance that may be required for tailoring effective rotavirus vaccines. Published in 2004 by John Wiley & Sons, Ltd.
Epidemiological and clinical aspects of human papillomavirus detection in the prevention of cervical cancer
Authors: Bekkers Ruud L. M. , Massuger Leon F. A. G. , Bulten Johan , Melchers Willem J. G. 
Published: March 2004

AbstractCervical cancer is a major cause of death, and the second most frequent cancer in women worldwide. Many studies have indicated a causal relation between genital human papillomavirus (HPV) infections and cervical cancer. High‐risk HPV genotypes have been detected in almost 100% of all cervical cancers, and the process of HPV mediated carcinogenesis has been partly clarified. The concept that HPV is a obligatory cause in cervical cancer development has lead to extensive research regarding the incorporation of HPV detection in (1) cervical cancer prevention programs, (2) triage of women with abnormal cervical scrapes in the screening program, and (3) follow‐up of patients treated for cervical intraepithelial neoplasia (CIN).Epidemiological studies indicate that 50% of women becoming sexually active contract a genital HPV infection within 2 years. The lifetime risk of a genital HPV infection is estimated to be 80%, but very few of these women will develop cervical cancer. Several studies have shown that the persistence of genital HPV infections is especially related to the development of cervical cancer. As a result, HPV detection at a single moment was shown to be of limited clinical value in the triage of patients with abnormal cervical scrapes, or during follow‐up after treatment for CIN. Furthermore, major variations in the sensitivity of different HPV detection methods, as well as differences in HPV detection related to the menstrual cycle, have shown that many facts regarding HPV transmission, replication, and detection need to be clarified, before HPV detection can be of clinical value. Copyright © 2004 John Wiley & Sons, Ltd.
The molecular basis of HIV capsid assembly—five years of progress
Authors: Adamson Catherine S. , Jones Ian M. 
Published: March 2004

AbstractThe assembly of HIV is relatively poorly investigated when compared with the process of virus entry. Yet a detailed understanding of the mechanism of assembly is fundamental to our knowledge of the complete life cycle of this virus and also has the potential to inform the development of new antiviral strategies. The repeated multiple interaction of the basic structural unit, Gag, might first appear to be little more than concentration dependent self‐assembly but the precise mechanisms emerging for HIV are far from simple. Gag interacts not only with itself but also with host cell lipids and proteins in an ordered and stepwise manner. It binds both the genomic RNA and the virus envelope protein and must do this at an appropriate time and place within the infected cell. The assembled virus particle must successfully release from the cell surface and, whilst being robust enough for transmission between hosts, must nonetheless be primed for rapid disassembly when infection occurs. Our current understanding of these processes and the domains of Gag involved at each stage is the subject of this review. Copyright © 2004 John Wiley & Sons, Ltd.
Valency of antibody binding to virions and its determination by surface plasmon resonance
Authors: Dimmock Nigel J. , Hardy Sam A. 
Published: March 2004

AbstractAll IgGs are homobivalent, but their ability to bind bivalently to the surface of a virus particle depends mainly on a favourable spacing of cognate epitopes and the angle that the FAb arm makes with the virus surface. If the angle of binding forces the second FAb arm to point into solution, monovalent binding is inevitable. This IgG will have the same affinity as its FAb, will be less stably bound than if it were bound bivalently, cannot cross‐link epitopes on the surface of a virion, and cannot neutralise by cross‐linking surface proteins. However, at moderate IgG concentrations, monovalently bound IgG can reduce infectivity by aggregating virions, a phenomenon that cannot occur with IgG bound bivalently. This review describes how surface plasmon resonance can be used to determine the valency of IgG binding to enveloped and non‐enveloped virus particles, and discusses the implications of this new methodology. Copyright © 2004 John Wiley & Sons, Ltd.
Specific recognition of virus‐infected cells by paired NK receptors
Authors: Arase Hisashi , Lanier Lewis L. 
Published: March 2004

AbstractNK cells show cytotoxicity and cytokine production upon recognition of virus‐infected cells and play an important role in conferring protective immunity against virus infection. Patients who lack functional NK cells are susceptible to severe infectious diseases such as herpesvirus infection. In addition, when NK cells are removed from cytomegalovirus‐resistant mice, the virus titre after infection is markedly increased and the mice are likely to die due to infection. However, the exact mechanism of how NK cells recognise virus‐infected cells has remained unclear for a long time. Recent findings of the presence of virus‐specific NK cell receptors and their ligands on virus‐infected cells have provided a new vision of a protective role of NK cells in virus infection. Furthermore, the recognition of virus‐infected cells by paired receptors consisting of activating and inhibitory receptors was found to correlate with the degree of host susceptibility to virus infection. Current topics on the role of NK cells in anti‐virus immunity are reviewed. Copyright © 2004 John Wiley & Sons, Ltd.
Estimating equations for association structures
Authors: Yan Jun , Fine Jason 
Published: March 2004

AbstractThis paper investigates generalized estimating equations for association parameters, which are frequently of interest in family studies, with emphasis on covariance estimation. Separate link functions are used to connect the mean, the scale, and the correlation to linear predictors involving possibly different sets of covariates, and separate estimating equations are proposed for the three sets of parameters. Simulations show that the robust ‘sandwich’ variance estimator and the jackknife variance estimator for the correlation parameters are generally close to the empirical variance for the sample size of 50 clusters. The results contradict Ziegleret al. and Kastner and Ziegler, where the ‘sandwich’ estimator obtained from the software MAREG was shown to be unsuitable for practical usage. The problem appears to arise because the MAREG variance estimator does not account for variability in estimation of the scale parameters, but may be valid with fixed scale. We also find that the formula for the approximate jackknife variance estimator in Ziegleret al. is deficient, resulting in systematic deviations from the fully iterated jackknife variance estimator. A general jackknife formula is provided and performs well in numerical studies. Data from a study on the genetics of alcoholism is used to illustrate the importance of reliable variance estimation in biomedical applications. Copyright © 2004 John Wiley & Sons, Ltd.
On the estimation of the binomial probability in multistage clinical trials
Authors: Jung Sin‐Ho , Kim Kyung Mann 
Published: March 2004

AbstractDue to the optional sampling effect in a sequential design, the maximum likelihood estimator (MLE) following sequential tests is generally biased. In a typical two‐stage design employed in a phase II clinical trial in cancer drug screening, a fixed number of patients are enrolled initially. The trial may be terminated for lack of clinical efficacy of treatment if the observed number of treatment responses after the first stage is too small. Otherwise, an additional fixed number of patients are enrolled to accumulate additional information on efficacy as well as on safety. There have been numerous suggestions for design of such two‐stage studies. Here we establish that under the two‐stage design the sufficient statistic, i.e. stopping stage and the number of treatment responses, for the parameter of the binomial distribution is also complete. Then, based on the Rao–Blackwell theorem, we derive the uniformly minimum variance unbiased estimator (UMVUE) as the conditional expectation of an unbiased estimator, which in this case is simply the maximum likelihood estimator based only on the first stage data, given the complete sufficient statistic. Our results generalize to a multistage design. We will illustrate features of the UMVUE based on two‐stage phase II clinical trial design examples and present results of numerical studies on the properties of the UMVUE in comparison to the usual MLE. Copyright © 2004 John Wiley & Sons, Ltd.
Goodness‐of‐fit tests for ordinal response regression models
Authors: Pulkstenis Erik , Robinson Timothy J. 
Published: March 2004

AbstractIt is well documented that the commonly used Pearson chi‐square and deviance statistics are not adequate for assessing goodness‐of‐fit in logistic regression models when continuous covariates are modelled. In recent years, several methods have been proposed which address this shortcoming in the binary logistic regression setting or assess model fit differently. However, these techniques have typically not been extended to the ordinal response setting and few techniques exist to assess model fit in that case. We present the modified Pearson chi‐square and deviance tests that are appropriate for assessing goodness‐of‐fit in ordinal response models when both categorical and continuous covariates are present. The methods have good power to detect omitted interaction terms and reasonable power to detect failure of the proportional odds assumption or modelling the wrong functional form of a continuous covariate. These tests also provide immediate information as to where a model may not fit well. In addition, the methods are simple to understand and implement, and are non‐specific. That is, they do not require prespecification of a type of lack‐of‐fit to detect. Copyright © 2004 John Wiley & Sons, Ltd.
Estimation of magnitude in gene–environment interactions in the presence of measurement error
Authors: Wong M. Y. , Day N. E. , Luan J. A. , Wareham N. J. 
Published: March 2004

AbstractThe design of studies aimed at identifying the interaction between genetic and environmental determinants in disease risk is attracting increased attention. In this paper, we study the effect of errors on measuring exposures and the effect of assessing genotype at one locus on the association of a continuous outcome measure with continuous exposures and genotype. The estimation of misclassification errors in assessing genotypes from a separate study is proposed.If the exposure measurement error is substantial, then even relatively small errors in genotyping within limits that are often quoted can have an appreciable effect on interaction estimates. We, thus, consider a method for correcting the measurement errors when the interaction between the exposures and the genetic factor is significant. Finally, we present an epidemiological example to demonstrate the importance of correcting measurement errors. Copyright © 2004 John Wiley & Sons, Ltd.
Pseudo‐likelihood estimation for a marginal multivariate survival model
Authors: Tibaldi Fabián , Molenberghs Geert , Burzykowski Tomasz , Geys Helena 
Published: March 2004

AbstractIn this paper, we propose a multivariate Plackett–Dale model for survival outcomes. A pseudo‐likelihood method for the estimation of the parameters is proposed and these ideas are applied to two case studies. The modelling approach is similar in spirit but different from Parner's approach. The first study is in AIDS, where the overall survival time and different opportunistic infections in HIV‐infected patients are studied. The second study is on adoption data where the association of the survival times within families is modelled, illustrating the use of the proposed methodology for the context of population genetics. Copyright © 2004 John Wiley & Sons, Ltd.
Comparing completely and stratified randomized designs in cluster randomized trials when the stratifying factor is cluster size: a simulation study
Authors: Lewsey J. D. 
Published: March 2004

AbstractStratified randomized designs are popular in cluster randomized trials (CRTs) because they increase the chance of the intervention groups being well balanced in terms of identified prognostic factors at baseline and may increase statistical power. The objective of this paper is to assess the gains in power obtained by stratifying randomization by cluster size, when cluster size is associated with an important cluster level factor which is otherwise unaccounted for in data analysis. A simulation study was carried out using a CRT where UK general practices were the randomized units as a template. The results show that when cluster size is strongly associated with a cluster level factor which is predictive of outcome, the stratified randomized design has superior power results to the completely randomized design and that the superiority is related to the number of clusters. Copyright © 2004 John Wiley & Sons, Ltd.
Predicting meningococcal disease outbreaks in structured populations
Authors: Ranta J. , Mäkelä P. H. , Arjas E. 
Published: March 2004

AbstractRational decision making on whether some form of intervention would be necessary to control the spread of a meningococcal epidemic is based on predictions concerning its potential natural progression. Unfortunately, reliable predictions are difficult to make during the early stages of an outbreak. A stochastic discrete time epidemic model was applied to adaptively predict the development of outbreaks of meningococcal disease in ‘closed’ populations such as military garrisons or boarding schools, which are further divided into subgroups called ‘units’. The performance of the adaptive method was assessed by using 3 simulated epidemics representing substantially different realizations in a ‘garrison’ of 20 units, with 68 men in each. Predictions of the weekly number of disease cases, of the number of carriers, and of the number of new infections were computed. Simulations suggest that predictions based only on the observed numbers of disease cases are generally inaccurate. These predictions can be improved if temporal observations on asymptomatic carriers in different units are utilized together with observed time series of the disease. A sample of 15 per cent from all units can be sufficient for a major improvement if the alternative is to obtain a full sample of only some units. Exploiting fully such information requires computer intensive Markov chain Monte Carlo methods. Copyright © 2004 John Wiley & Sons, Ltd.
Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer
Authors: Royston Patrick , Parmar Mahesh K. B. , Sylvester Richard 
Published: March 2004

AbstractMany models for clinical prediction (prognosis or diagnosis) are published in the medical literature every year but few such models find their way into clinical practice. The reason may be that since in most cases models have not been validated in independent data, they lack generality and/or credibility. In this paper we consider the situation in which several compatible, independent data sets relating to a given disease with a time‐to‐event endpoint are available for analysis. The aim is to construct and evaluate a single prognostic model. Building a multivariable model from the available prognostic factors is accomplished within the Cox proportional hazards framework, stratifying by study. Non‐linear relationships with continuous predictors are modelled by using fractional polynomials. To assess the discrimination or separation of a survival model, we use theDstatistic of Royston and Sauerbrei.Dmay be interpreted as the separation (log hazard ratio) between the survival distributions for two independent prognostic groups. To evaluate the generality of a prognostic model across the data sets, we propose ‘internal–external cross‐validation’ onD: each study is omitted in turn, the model parameters are estimated from the remaining studies andDis evaluated in the omitted study. Because the linear predictor of a survival model tells only part of the story, we also suggest a method for investigating heterogeneity in the baseline distribution function across studies which involves fitting completely specified, flexible parametric survival models (Royston and Parmar). Our final models combine the prognostic index (obtained with stratification by study) with the pooled baseline survival distribution (estimated parametrically). By applying this methodology, we construct two prognostic scores in superficial bladder cancer. The simpler of the two scores is more suited to clinical application. We show that a three‐group prognostic classification scheme based on either score produces well‐separated survival curves for each of the data sets, despite identifiable heterogeneity among the baseline distribution functions and to a lesser extent among the prognostic indexes for the individual studies. Copyright © 2004 John Wiley & Sons, Ltd.
Modelling of cardiac imaging data with spatial correlation
Authors: Bowman F. DuBois , Waller Lance A. 
Published: March 2004

AbstractCardiac imaging with single photon emission computed tomography (SPECT) is a common approach for quantifying myocardial perfusion. Fusing serial SPECT studies allows detection and quantification of changes in myocardial perfusion such as those resulting from disease progression or successful treatment therapy for patients with coronary artery disease. The abundance of data for each subject along with the inherent intra‐subject correlation due to spatial proximity of multiple perfusion measurements present special analytical challenges. We utilize a standard physiological model of the left ventricle (LV) to construct a general statistical model for cardiac perfusion that incorporates spatial correlation. We illustrate the use of mixed effects models and linear models with correlated errors to estimate myocardial perfusion counts and to compare these counts across serial studies. We address different types of spatial correlation among perfusion measurements in the LV, and we consider various parametric structures for these correlations. We apply the model to data from serial SPECT studies conducted while subjects were in both restful and stressful states approximately two days and one year following a myocardial infarction. Copyright © 2004 John Wiley & Sons, Ltd.
A testbed for performance evaluation of load‐balancing strategies for Web server systems
Authors: Sanghi Dheeraj , Jalote Pankaj , Agarwal Puneet , Jain Nitin , Bose Supriyo 
Published: March 2004

AbstractTo improve response time of a Web site, one replicates the site on multiple servers. The effectiveness of a replicated server system will depend on how the incoming requests are distributed among replicas. A large number of load‐balancing strategies for Web server systems have been proposed.In this paper we describe a testbed that can be used to evaluate the performance of different load‐balancing strategies. The testbed uses a general architecture which allows different load‐balancing approaches to be supported easily. It emulates a typical World Wide Web scenario and allows variable load generation and performance measurement. We have performed some preliminary experiments to measure the performance of a few policies for load balancing using this testbed. Copyright © 2003 John Wiley & Sons, Ltd.