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At least 1,135 records · Page 63Linked to original sources
PubMed2003

Using a model for structured reflection on palliative care nursing: exploring the challenges raised.

Reflection on palliative care nursing practice has to encompass every dimension of the holistic care we offer. In this article a possible structured model for reflection on palliative care nursing is discussed and used to reflect on the care given during a community Macmillan nurse visit. The reflection revealed a number of challenges. These included the possible conflict between patient autonomy and quality of life for carers; the role of intuition in palliative nursing and spiritual care. The article concludes that reflection has a role to play in exploring the innate tensions in palliative care, voicing the often silent intuitive knowledge and promoting expertise in spiritual care.

Attitude of Health Personnel↗
PubMed2007

Mediational analysis in HIV/AIDS research: estimating multivariate path analytic models in a structural equation modeling framework.

Mediational analyses have been recognized as useful in answering two broad questions that arise in HIV/AIDS research, those of theoretical model testing and of the effectiveness of multicomponent interventions. This article serves as a primer for those wishing to use mediation techniques in their own research, with a specific focus on mediation applied in the context of path analysis within a structural equation modeling (SEM) framework. Mediational analyses and the SEM framework are reviewed at a general level, followed by a discussion of the techniques as applied to complex research designs, such as models with multiple mediators, multilevel or longitudinal data, categorical outcomes, and problematic data (e.g., missing data, nonnormally distributed variables). Issues of statistical power and of testing the significance of the mediated effect are also discussed. Concrete examples that include computer syntax and output are provided to demonstrate the application of these techniques to testing a theoretical model and to the evaluation of a multicomponent intervention.

Data Interpretation, Statistical↗
PubMed2003

Generalized semiparametrically structured ordinal models.

Semiparametrically structured models are defined as a class of models for which the predictors may contain parametric parts, additive parts of covariates with an unspecified functional form, and interactions which are described as varying coefficients. In the case of an ordinal response the complexity of the predictor is determined by different sorts of effects. Global effects and category-specific effects are distinguished; the latter allow the effect to vary across response categories. A general framework is developed in which global as well as category-specific effects may have unspecified functional form. The framework extends various existing methods of modeling ordinal responses. The Wilkinson-Rogers notation is extended to incorporate smooth model parts and varying coefficient terms, the latter being important for the smooth specification of category-specific effects.

Anti-Inflammatory Agents↗
PubMed1993

Numerical solution of structured population models. I. Age structure.

Numerical methods are presented for a general age-structured population model with demographic rates depending on age and the total population size. The accuracy of these methods is established by solving problems for which alternate solution techniques are available and are used for comparison. The methods reliably solve test problems with a variety of dynamic behavior. Simulations of a blowfly population exhibit cyclic fluctuations, whereas a simulated squirrel population reaches a stable age distribution and stable equilibrium population size. Life-history attributes are easily studied from the computed solutions, and are discussed for these examples. Recovery of a stressed population back to equilibrium is examined by computing the transition in age structure, and the transient behavior of other properties of the population such as the per capita growth rate, the average age, and the generation length.

Aging↗
PubMed2004

Automated clustering of ensembles of alternative models in protein structure databases.

Experimentally determined protein structures have been classified in different public databases according to their structural and evolutionary relationships. Frequently, alternative structural models, determined using X-ray crystallography or NMR spectroscopy, are available for a protein. These models can present significant structural dissimilarity. Currently there is no classification available for these alternative structures. In order to classify them, we developed STRuster, an automated method for clustering ensembles of structural models according to their backbone structure. The method is based on the calculation of carbon alpha (Calpha) distance matrices. Two filters are applied in the calculation of the dissimilarity measure in order to identify both large and small (but significant) backbone conformational changes. The resulting dissimilarity value is used for hierarchical clustering and partitioning around medoids (PAM). Hierarchical clustering reflects the hierarchy of similarities between all pairs of models, while PAM groups the models into the 'optimal' number of clusters. The method has been applied to cluster the structures in each SCOP species level and can be easily applied to any other sets of conformers. The results are available at: http://bioinf.mpi-sb.mpg.de/projects/struster/.

Aldehyde-Lyases↗
PubMed2003

On specifying the null model for incremental fit indices in structural equation modeling.

In structural equation modeling, incremental fit indices are based on the comparison of the fit of a substantive model to that of a null model. The standard null model yields unconstrained estimates of the variance (and mean, if included) of each manifest variable. For many models, however, the standard null model is an improper comparison model. In these cases, incremental fit index values reported automatically by structural modeling software have no interpretation and should be disregarded. The authors explain how to formulate an acceptable, modified null model, predict changes in fit index values accompanying its use, provide examples illustrating effects on fit index values when using such a model, and discuss implications for theory and practice of structural equation modeling.

Data Interpretation, Statistical↗
PubMed2003

Assessing individual bioequivalence using the structural equation model.

The structural equation model (SEM) is introduced as a useful approach for assessing individual bio-equivalence. SEM parameters are estimated using a partial likelihood analysis and the hypotheses of individual bioequivalence is evaluated in a disaggregate way, testing separately the hypothesis concerning SEM parameters, and assessing the overall hypothesis of individual bioequivalence using the intersection-union principle. Limits of bioequivalence for SEM parameters are proposed and a power analysis is carried out.

Biological Availability↗
PubMed2006

Comparing groups on latent variables: a structural equation modeling approach.

Structural equation modeling (SEM) provides a dependable framework for testing differences among groups on latent variables (constructs, factors). The purpose of this article is to illustrate SEM-based testing for group mean differences on latent variables. Related procedures of confirmatory factor analysis and testing for measurement invariance across compared groups are also presented in the context of rehabilitation research.

Analysis of Variance↗
PubMed1998

An empirical comparison of lead exposure pathway models.

Structural equation modeling is a statistical method for partitioning the variance in a set of interrelated multivariate outcomes into that which is due to direct, indirect, and covariate (exogenous) effects. Despite this model's flexibility to handle different experimental designs, postulation of a causal chain among the endogenous variables and the points of influence of the covariates is required. This has motivated the researchers at the University of Cincinnati Department of Environmental Health to be guided by a theoretical model for movement of lead from distal sources (exterior soil or dust and paint lead) to proximal sources (interior dust lead) and then finally to biologic outcomes (handwipe and blood lead). The question of whether a single structural equation model built from proximity arguments can be applied to diverse populations observed in different communities with varying lead amounts, sources, and bioavailabilities is addressed in this article. This reanalysis involved data from 1855 children less than 72 months of age enrolled in 11 studies performed over approximately 15 years. Data from children residing near former ore-processing sites were included in this reanalysis. A single model adequately fit the data from these 11 studies; however, the model needs to be flexible to include pathways that are not frequently observed. As expected, the more proximal sources of interior dust lead and handwipe lead were the most important predictors of blood lead; soil lead often had a number of indirect influences. A limited number of covariates were also isolated as usually affecting the endogenous lead variables. The blood lead levels surveyed at the ore-processing sites were comparable to and actually somewhat lower than those reported in the the Third National Health and Nutrition Examination Survey. Lessened bioavailability of the lead at certain of these sites is a probable reason for this finding.

Child, Preschool↗
PubMed2006

Building a better model: an introduction to structural equation modelling.

Confirmatory factor analysis (CFA) and structural equation modelling (SEM) are powerful extensions of path analysis, which was described in a previous article in this series. CFA differs from the more traditional exploratory factor analysis in that the relations among the variables are specified a priori, which permits more powerful tests of construct validity for scales. It can also be used to compare different versions of a scale (for example, English and French) and to determine whether the scale performs equivalently in different groups (for example, men and women). SEM expands on path analysis by allowing paths to be drawn between latent variables (which, in other techniques, are called factors or hypothetical constructs), that is, variables that are not seen directly but, rather, through their effect on observable variables, such as questionnaires and behavioural measures. Each latent variable and its associated measured variables form small CFAs, with the added advantage that the correlations among the variables can be corrected for the unreliability of the measures.

Major Depressive Disorder↗
PubMed1997

[A new wave of behavior genetic modeling using covariance structure analysis].

A number of useful methods for analyzing covariance structure have been proposed in the studies of human behavior genetics, reflecting the fact that the behavior genetic studies are one of the main origins of covariance structure model. In this paper, I review recent progress on methodology for behavior genetic studies of twins and families from the standpoint of the structural equation modeling. Especially, genetic ACE (additive genetic, common environment and random environment) model, multivariate ACE model, genetic factor analysis model and twin-parent model are focused upon. This review also discusses how to construct applied structural equation models which are useful for psychological research.

Factor Analysis, Statistical↗
PubMed2005

Refinement of protein cores and protein-peptide interfaces using a potential scaling approach.

Refinement of side chain conformations in protein model structures and at the interface of predicted protein-protein or protein-peptide complexes is an important step during protein structural modelling and docking. A common approach for side chain prediction is to assume a rigid protein main chain for both docking partners and search for an optimal set of side chain rotamers to optimize the steric fit. However, depending on the target-template similarity in the case of comparative protein modelling and on the accuracy of an initially docked complex, the main chain template structure is only an approximation of a realistic target main chain. An inaccurate rigid main chain conformation can in turn interfere with the prediction of side chain conformations. In the present study, a potential scaling approach (PS-MD) during a molecular dynamics (MD) simulation that also allows the inclusion of explicit solvent has been used to predict side chain conformations on semi-flexible protein main chains. The PS-MD method converges much faster to realistic protein-peptide interface structures or protein core structures than standard MD simulations. Depending on the accuracy of the protein main chain, it also gives significantly better results compared with the standard rotamer search method.

Amino Acid Sequence↗
PubMed2004

Mechanism of membrane binding of the phospholipase D1 PX domain.

Mammalian phospholipases D (PLD), which catalyze the hydrolysis of phosphatidylcholine to phosphatidic acid (PA), have been implicated in various cell signaling and vesicle trafficking processes. Mammalian PLD1 contains two different membrane-targeting domains, pleckstrin homology and Phox homology (PX) domains, but the precise roles of these domains in the membrane binding and activation of PLD1 are still unclear. To elucidate the role of the PX domain in PLD1 activation, we constructed a structural model of the PX domain by homology modeling and measured the membrane binding of this domain and selected mutants by surface plasmon resonance analysis. The PLD1 PX domain was found to have high phosphoinositide specificity, i.e. phosphatidylinositol 3,4,5-trisphosphate (PtdIns-(3,4,5)P(3)) >> phosphatidylinositol 3-phosphate > phosphatidylinositol 5-phosphate >> other phosphoinositides. The PtdIns(3,4,5)P(3) binding was facilitated by the cationic residues (Lys(119), Lys(121), and Arg(179)) in the putative binding pocket. Consistent with the model structure that suggests the presence of a second lipid-binding pocket, vesicle binding studies indicated that the PLD1 PX domain could also bind with moderate affinity to PA, phosphatidylserine, and other anionic lipids, which were mediated by a cluster of cationic residues in the secondary binding site. Simultaneous occupancy of both binding pockets synergistically increases membrane affinity of the PX domain. Electrostatic potential calculations suggest that a highly positive potential near the secondary binding site may facilitate the initial adsorption of the domain to the anionic membrane, which is followed by the binding of PtdIns(3,4,5)P(3) to its binding pocket. Collectively, our results suggest that the interaction of the PLD1 PX domain with PtdIns(3,4,5)P(3) and/or PA (or phosphatidylserine) may be an important factor in the spatiotemporal regulation and activation of PLD1.

Amino Acid Sequence↗
PubMed2003

Deciphering a novel thioredoxin-like fold family.

Sequence--and structure-based searching strategies have proven useful in the identification of remote homologs and have facilitated both structural and functional predictions of many uncharacterized protein families. We implement these strategies to predict the structure of and to classify a previously uncharacterized cluster of orthologs (COG3019) in the thioredoxin-like fold superfamily. The results of each searching method indicate that thioltransferases are the closest structural family to COG3019. We substantiate this conclusion using the ab initio structure prediction method rosetta, which generates a thioredoxin-like fold similar to that of the glutaredoxin-like thioltransferase (NrdH) for a COG3019 target sequence. This structural model contains the thiol-redox functional motif CYS-X-X-CYS in close proximity to other absolutely conserved COG3019 residues, defining a novel thioredoxin-like active site that potentially binds metal ions. Finally, the rosetta-derived model structure assists us in assembling a global multiple-sequence alignment of COG3019 with two other thioredoxin-like fold families, the thioltransferases and the bacterial arsenate reductases (ArsC).

Amino Acid Sequence↗
PubMed2000

Production and characterization of the functional fragment of pneumococcal surface protein A.

Pneumococcal surface protein A (PspA) is present on the cell wall of Streptococcus pneumoniae pathogen and has an antigenetically variable N-terminal domain. This aminoterminal domain is essential for full pneumococcal virulence, and monoclonal antibodies raised against it protect mice against pneumococcal infections. We have cloned and expressed a 34-kDa N-terminal fragment of PspA in Escherichia coli in a soluble form using the T7 RNA polymerase pET-20b vector system. Nickel chelate affinity purification followed by size exclusion and anion exchange chromatography yielded large amounts of pure and homogeneous protein. Analytical ultracentrifugation sedimentation velocity band and boundary studies showed that the molecule was present in aqueous solutions in a monomeric form with an axial shape ratio of approximately 1:12, typical of fibrous proteins. Sequence analyses indicated an alpha-helical coiled-coil structure for this monomeric molecule with only few loop-type breaks in helicity. The mostly alpha-helical structure of this PspA construct was consistent with circular dichroism spectroscopy data. Based on the ultracentrifugation studies, the circular dichroism spectra, and the PspA's sequence analyses, two structural models for the amino-terminal part of the PspA molecule are proposed. The evident highly charged and polar character of the surface of the modeled structures suggests functional properties of PspA that are related to the prevention of S. pneumoniae interactions with the host complement system.

Amino Acid Sequence↗
PubMed2000

Synthetic peptide mimicking of binding sites on olfactory receptor protein for use in 'electronic nose'.

A putative tertiary structure model of the dog's olfactory receptor (olfd canfa) is established in this study. By using a target odorous compound (trimethylamine), it is possible to locate the most plausible binding sites between the receptor model structure and the target odorous molecules through computer docking simulations. The two short oligo-peptide sequences (orp61 and orp188) for trimethylamine sensing were identified, synthesized, purified and coated onto the surface of the separate piezoelectric gold electrodes. These two peptides show a high binding capability for trimethylamine. To further enhance the sensitivity of the polypeptides towards the target compound, the polarity and the degree of docking were changed by a site-specific modification technique. The orp61 sequence was modified by substituting two amino acids in the binding pocket resulting in 33% increase in sensitivity towards trimethylamine and reduced noises from other non-target chemicals. The techniques used in the present study offer a unique approach for synthesizing peptides in mimicking binding domain of olfactory receptors. The approach can be easily applied to further development of recognized molecules for gas sensing, especially for use in 'electronic noses'.

Amino Acid Sequence↗
PubMed2004

Bayesian model comparison of nonlinear structural equation models with missing continuous and ordinal categorical data.

Missing data are very common in behavioural and psychological research. In this paper, we develop a Bayesian approach in the context of a general nonlinear structural equation model with missing continuous and ordinal categorical data. In the development, the missing data are treated as latent quantities, and provision for the incompleteness of the data is made by a hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm. We show by means of a simulation study that the Bayesian estimates are accurate. A Bayesian model comparison procedure based on the Bayes factor and path sampling is proposed. The required observations from the posterior distribution for computing the Bayes factor are simulated by the hybrid algorithm in Bayesian estimation. Our simulation results indicate that the correct model is selected more frequently when the incomplete records are used in the analysis than when they are ignored. The methodology is further illustrated with a real data set from a study concerned with an AIDS preventative intervention for Filipina sex workers.

Algorithms↗