Binding of bisubstrate analog promotes large structural changes in the unregulated catalytic trimer of aspartate transcarbamoylase: Implications for allosteric regulation

A central problem in understanding enzyme regulation is to define the conformational states that account for allosteric changes in catalytic activity. For Escherichia coli aspartate transcarbamoylase (ATCase; EC 2.1.3.2) the active, relaxed (R state) holoenzyme is generally assumed to be represented by the crystal structure of the complex of the holoenzyme with the bisubstrate analog N-phosphonacetyl-l-aspartate (PALA). It is unclear, however, which conformational differences between the unliganded, inactive, taut (T state) holoenzyme and the PALA complex are attributable to localized effects of inhibitor binding as contrasted to the allosteric transition. To define the conformational changes in the isolated, nonallosteric C trimer resulting from the binding of PALA, we determined the 1.95-Å resolution crystal structure of the C trimer–PALA complex. In contrast to the free C trimer, the PALA-bound trimer exhibits approximate threefold symmetry. Conformational changes in the C trimer upon PALA binding include ordering of two active site loops and closure of the hinge relating the N- and C-terminal domains. The C trimer–PALA structure closely resembles the liganded C subunits in the PALA-bound holoenzyme. This similarity suggests that the pronounced hinge closure and other changes promoted by PALA binding to the holoenzyme are stabilized by ligand binding. Consequently, the conformational changes attributable to the allosteric transition of the holoenzyme remain to be defined.

Crystal structure of a Staphylococcus aureus protein A domain complexed with the Fab fragment of a human IgM antibody: Structural basis for recognition of B-cell receptors and superantigen activity

Staphylococcus aureus produces a virulence factor, protein A (SpA), that contains five homologous Ig-binding domains. The interactions of SpA with the Fab region of membrane-anchored Igs can stimulate a large fraction of B cells, contributing to lymphocyte clonal selection. To understand the molecular basis for this activity, we have solved the crystal structure of the complex between domain D of SpA and the Fab fragment of a human IgM antibody to 2.7-Å resolution. In the complex, helices II and III of domain D interact with the variable region of the Fab heavy chain (VH) through framework residues, without the involvement of the hypervariable regions implicated in antigen recognition. The contact residues are highly conserved in human VH3 antibodies but not in other families. The contact residues from domain D also are conserved among all SpA Ig-binding domains, suggesting that each could bind in a similar manner. Features of this interaction parallel those reported for staphylococcal enterotoxins that are superantigens for many T cells. The structural homology between Ig VH regions and the T-cell receptor Vβ regions facilitates their comparison, and both types of interactions involve lymphocyte receptor surface remote from the antigen binding site. However, T-cell superantigens reportedly interact through hydrogen bonds with T-cell receptor Vβ backbone atoms in a primary sequence-independent manner, whereas SpA relies on a sequence-restricted conformational binding with residue side chains, suggesting that this common bacterial pathogen has adopted distinct molecular recognition strategies for affecting large sets of B and T lymphocytes.

Structure and evolution of the compact radio source in NGC 1275.

Investigations of the fine-scale structure in the compact nucleus of the radio source 3C 84 in NGC 1275 (New General Catalogue number) are reported. Structural monitoring observations beginning as early as 1976, and continuing to the present, revealed subluminal motions in a jet-like relatively diffuse region extending away from a flat-spectrum core. A counterjet feature was discovered in 1993, and very recent nearly simultaneous studies have detected the same feature at five frequencies ranging from 5 to 43 GHz. The counterjet exhibits a strong low-frequency cutoff, giving this region of the source an inverted spectrum. The observations are consistent with a physical model in which the cutoff arises from free-free absorption in a volume that surrounds the core but obscures only the counterjet feature. If such a model is confirmed, very-long-baseline radio interferometry observations can then be used to probe the accretion region, outside the radio jet, on parsec scales.

The Spanish version of the Prenatal Breast-feeding Self-efficacy Scale: Reliability and validity assessment

Background: Only a minority of infants are exclusively breastfed for the recommended 6 months postpartum. Breast-feeding self-efficacy is a mother's confidence in her ability to breastfeed and is predictive of breastfeeding behaviors. The Prenatal Breast-feeding Self-efficacy Scale (PBSES) was developed among English-speaking mothers to measure breastfeeding self-efficacy before delivery. Objectives: To translate the PBSES into Spanish and assess its psychometric properties. Design: Reliability and validity assessment. Setting: A public hospital in Yecla, Spain. Participants: A convenience sample of 234 pregnant women in their third trimester of pregnancy. Methods: The PBSES was translated into Spanish using forward and back translation. A battery of self-administered questionnaires was completed by participants, including a questionnaire on sociodemographic variables, breastfeeding experience and intention, as well as the Spanish version of the PBSES. Also, data on exclusive breastfeeding at discharge were collected from hospital database. Dimensional structure, internal consistency and construct validity of the Spanish version of PBSES were assessed. Results: Confirmatory factor analysis suggested the presence of one construct, self-efficacy, with four dimensions or latent variables. Cronbach's alpha coefficient for internal consistency was 0.91. Response patterns based on decision to breastfeed during pregnancy provided evidence of construct validity. In addition, the scores of the Spanish version of the PBSES significantly predicted exclusive breastfeeding at discharge. Conclusions: The Spanish version of PBSES shows evidences of reliability, and contrasting group and predictive validity. Confirmatory factor analysis indicated marginal fit and further studies are needed to provide new evidence on the structure of the scale. The Spanish version of the PBSES can be considered a reliable measure and shows validity evidences.

Development and psychometric testing of the clinical learning environment, supervision and nurse teacher evaluation scale (CLES+T): The Spanish version

Background: The Clinical Learning Environment, Supervision and Nurse Teacher scale is a reliable and valid instrument to evaluate the quality of the clinical learning process in international nursing education contexts. Objectives: This paper reports the development and psychometric testing of the Spanish version of the Clinical Learning Environment, Supervision and Nurse Teacher scale. Design: Cross-sectional validation study of the scale. Setting: 10 public and private hospitals in the Alicante area, and the Faculty of Health Sciences (University of Alicante, Spain). Participants: 370 student nurses on clinical placement (January 2011–March 2012). Methods: The Clinical Learning Environment, Supervision and Nurse Teacher scale was translated using the modified direct translation method. Statistical analyses were performed using PASW Statistics 18 and AMOS 18.0.0 software. A multivariate analysis was conducted in order to assess construct validity. Cronbach’s alpha coefficient was used to evaluate instrument reliability. Results: An exploratory factorial analysis identified the five dimensions from the original version, and explained 66.4% of the variance. Confirmatory factor analysis supported the factor structure of the Spanish version of the instrument. Cronbach’s alpha coefficient for the scale was .95, ranging from .80 to .97 for the subscales. Conclusion: This version of the Clinical Learning Environment, Supervision and Nurse Teacher scale instrument showed acceptable psychometric properties for use as an assessment scale in Spanish-speaking countries.

Validation of the Spanish version of mackey childbirth satisfaction rating scale

Background: The “Mackey Childbirth Satisfaction Rating Scale” (MCSRS) is a complete non-validated scale which includes the most important factors associated with maternal satisfaction. Our primary purpose was to describe the internal structure of the scale and validate the reliability and validity of concept of its Spanish version MCSRS-E. Methods: The MCSRS was translated into Spanish, back-translated and adapted to the Spanish population. It was then administered following a pilot test with women who met the study participant requirements. The scale structure was obtained by performing an exploratory factorial analysis using a sample of 304 women. The structures obtained were tested by conducting a confirmatory factorial analysis using a sample of 159 women. To test the validity of concept, the structure factors were correlated with expectations prior to childbirth experiences. McDonald’s omegas were calculated for each model to establish the reliability of each factor. The study was carried out at four University Hospitals; Alicante, Elche, Torrevieja and Vinalopo Salud of Elche. The inclusion criteria were women aged 18–45 years old who had just delivered a singleton live baby at 38–42 weeks through vaginal delivery. Women who had difficulty speaking and understanding Spanish were excluded. Results: The process generated 5 different possible internal structures in a nested model more consistent with the theory than other internal structures of the MCSRS applied hitherto. All of them had good levels of validation and reliability. Conclusions: This nested model to explain internal structure of MCSRS-E can accommodate different clinical practice scenarios better than the other structures applied to date, and it is a flexible tool which can be used to identify the aspects that should be changed to improve maternal satisfaction and hence maternal health.

Transcultural properties of the Composite Scale of Morningness: The relevance of the "morning affect" factor

Morningness scales have been translated into several languages, but it lack of normative data and methodological differences make cross-cultural comparisons difficult. This study examines the psychometric properties and factor structure of the Composite Scale of Morningness (CSM) in samples from five countries: France (n = 627), Italy (n, = 702), Spain (n = 391), Thailand (n. = 503), and Australia (17 = 654). Strong national differences are identified. A quadratic relationship between age and CSM total score was apparent in the Australian data with a downward trend after age 35 yrs. There was no age effect in air), sample in the range from 18 to 29 yrs. Factor analysis identified a three-factor solution in all groups for both men and women. Tucker's congruence coefficients indicate that: (1) this solution is highly congruent between sexes in each culture, and (2) a morning affect factor is highly congruent between cultures. These results indicate there are national differences in factorial structure and that cut-off scores used to categorize participants as morning- and evening-types should be established for different cultural and age groups.

Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome

Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did flat contain ail apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-rnRNA contamination during library construction, or alternatively represent nonspecific transcriptional noise. Here we Show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts Of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide Stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.

Influence of lattice interactions on the jahn-teller distortion of the [Cu(H2O)(6)](2+) ion: Dependence of the crystal structure of K-2[Cu(H2O)(6)](SO4)(2x)(SeO4)(2-2x) upon the sulfate/selenate ratio

The temperature dependence of the structure of the mixed-anion Tutton salt K-2[Cu(H2O)(6)](SO4)(2x)(SeO4)(2-2x) has been determined for crystals with 0, 17, 25, 68, 78, and 100% sulfate over the temperature range of 85-320 K. In every case, the [Cu(H2O)(6)](2+) ion adopts a tetragonally elongated coordination geometry with an orthorhombic distortion. However, for the compounds with 0, 17, and 25% sulfate, the long and intermediate bonds occur on a different pair of water molecules from those with 68, 78, and 100% sulfate. A thermal equilibrium between the two forms is observed for each crystal, with this developing more readily as the proportions of the two counterions become more similar. Attempts to prepare a crystal with approximately equal amounts of sulfate and selenate were unsuccessful. The temperature dependence of the bond lengths has been analyzed using a model in which the Jahn-Teller potential surface of the [Cu(H2O)(6)](2+) ion is perturbed by a lattice-strain interaction. The magnitude and sign of the orthorhombic component of this strain interaction depends on the proportion of sulfate to selenate. Significant deviations from Boltzmann statistics are observed for those crystals exhibiting a large temperature dependence of the average bond lengths, and this may be explained by cooperative interactions between neighboring complexes.

Translation of the flavivirus Kunjin NS3 gene in cis but not its RNA sequence or secondary structure is essential for efficient RNA packaging

Our previous studies using trans-complementation analysis of Kunjin virus (KUN) full-length cDNA clones harboring in-frame deletions in the NS3 gene demonstrated the inability of these defective complemented RNAs to be packaged into virus particles (W. J. Liu, P. L. Sedlak, N. Kondratieva, and A. A. Khromykh, J. Virol. 76:10766-10775). In this study we aimed to establish whether this requirement for NS3 in RNA packaging is determined by the secondary RNA structure of the NS3 gene or by the essential role of the translated NS3 gene product. Multiple silent mutations of three computer-predicted stable RNA structures in the NS3 coding region of KUN replicon RNA aimed at disrupting RNA secondary structure without affecting amino acid sequence did not affect RNA replication and packaging into virus-like particles in the packaging cell line, thus demonstrating that the predicted conserved RNA structures in the NS3 gene do not play a role in RNA replication and/or packaging. In contrast, double frameshift mutations in the NS3 coding region of full-length KUN RNA, producing scrambled NS3 protein but retaining secondary RNA structure, resulted in the loss of ability of these defective RNAs to be packaged into virus particles in complementation experiments in KUN replicon-expressing cells. Furthermore, the more robust complementation-packaging system based on established stable cell lines producing large amounts of complemented replicating NS3-deficient replicon RNAs and infection with KUN virus to provide structural proteins also failed to detect any secreted virus-like particles containing packaged NS3-deficient replicon RNAs. These results have now firmly established the requirement of KUN NS3 protein translated in cis for genome packaging into virus particles.

Structural ambiguity of the Chinese version of the Hospital Anxiety and Depression Scale in patients with coronary heart disease

Background The Hospital Anxiety and Depression Scale (HADS) is a widely used screening tool designed as a case detector for clinically relevant anxiety and depression. Recent studies of the HADS in coronary heart disease (CHD) patients in European countries suggest it comprises three, rather than two, underlying sub-scale dimensions. The factor structure of the Chinese version of the HADS was evaluated in patients with CHD in mainland China. Methods Confirmatory factor analysis (CFA) was conducted on self-report HADS forms from 154 Chinese CHD patients. Results Little difference was observed in model fit between best performing three-factor and two-factor models. Conclusion The current observations are inconsistent with recent studies highlighting a dominant underlying tri-dimensional structure to the HADS in CHD patients. The Chinese version of the HADS may perform differently to European language versions of the instrument in patients with CHD.

An examination of the psychometric properties of the Rosenberg Self-Esteem Scale (RSES) in Chinese acute coronary syndrome (ACS) patients

The psychometric properties of the Rosenberg Self-Esteem Scale (RSES) as a clinical research instrument for acute coronary syndrome (ACS) patients were investigated in a translated Chinese version of the instrument. A confirmatory factor analysis was conducted on the RSES to establish its psychometric properties in 128 ACS patients over two observation points (within 1 week and 6 months post-admission for ACS). Internal and test - retest reliability of the RSES-TOT (all-items) and RSES-POS sub-scale (positively valenced items) were found to be acceptable. The RSES-NEG sub-scale (negatively valenced items) lacked acceptable internal reliability. The underlying factor structure of the RSES comprised two distinct but related factors, though there was inconsistency in best model fit indices at the 1-week observation point. The use of the RSES as two sub-scales (RSES-POS and RSES-NEG) may be clinically useful in evaluating the influence of this important psychological construct on the health outcomes of patients with ACS. Directions for future research are indicated.

A Franco-British comparison of patterns of working hours in large-scale grocery retailing, with specific reference to part-time work

In this thesis patterns of working hours in large-scale grocery retailing in Britain and France are compared. The research is carried out using cross-national comparative methodology, and the analysis is based on information derived from secondary sources and empirical research in large-scale grocery retailing involving employers and trade unions at industry level and case studies at outlet level. The thesis begins by comparing national patterns of working hours in Britain and France over the post-war period. Subsequently, a detailed comparison of working hours in large-scale grocery retailing in Britain and France is carried out through the analysis of secondary sources and empirical data. Emphasis is placed on analyzing part-time working hours. They are contrasted and compared at national level and explained in terms of supply and demand factors. The relationships between the structuring of, and satisfaction with, working hours and factors determining women's integration in the workforce in Britain and France are investigated. Part-time hours are then compared and contrasted in large-scale grocery retailing in the context of the analysis of working hours. The relationship between the structuring of working hours and satisfaction with them is examined in both countries through research with women part-timers in case study outlets. The cross-national comparative methodology is used to examine whether dissimilar national contexts in Britain and France have led to different patterns of working hours in large-scale grocery retailing. The principal conclusion is that significant differences are found in the length, organization and flexibility of working hours and that these differences can be attributed to dissimilar socio-economic, political, and cultural contexts in the two countries.

An examination of the Prandtl mechanism in large dimension slope failures

An alternative explanation for the modes of failure of large scale failures of open pit walls to those of classical slope stability theory is proposed that makes use of the concept of a transition zone, which is described by a modified Prandtls prism.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.