6 resultados para Recent Structural Models

em Duke University


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Empirical modeling of high-frequency currency market data reveals substantial evidence for nonnormality, stochastic volatility, and other nonlinearities. This paper investigates whether an equilibrium monetary model can account for nonlinearities in weekly data. The model incorporates time-nonseparable preferences and a transaction cost technology. Simulated sample paths are generated using Marcet's parameterized expectations procedure. The paper also develops a new method for estimation of structural economic models. The method forces the model to match (under a GMM criterion) the score function of a nonparametric estimate of the conditional density of observed data. The estimation uses weekly U.S.-German currency market data, 1975-90. © 1995.

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BACKGROUND: The proportion of births attended by skilled health personnel is one of two indicators used to measure progress towards Millennium Development Goal 5, which aims for a 75% reduction in global maternal mortality ratios by 2015. Rwanda has one of the highest maternal mortality ratios in the world, estimated between 249-584 maternal deaths per 100,000 live births. The objectives of this study were to quantify secular trends in health facility delivery and to identify factors that affect the uptake of intrapartum healthcare services among women living in rural villages in Bugesera District, Eastern Province, Rwanda. METHODS: Using census data and probability proportional to size cluster sampling methodology, 30 villages were selected for community-based, cross-sectional surveys of women aged 18-50 who had given birth in the previous three years. Complete obstetric histories and detailed demographic data were elicited from respondents using iPad technology. Geospatial coordinates were used to calculate the path distances between each village and its designated health center and district hospital. Bivariate and multivariate logistic regressions were used to identify factors associated with delivery in health facilities. RESULTS: Analysis of 3106 lifetime deliveries from 859 respondents shows a sharp increase in the percentage of health facility deliveries in recent years. Delivering a penultimate baby at a health facility (OR = 4.681 [3.204 - 6.839]), possessing health insurance (OR = 3.812 [1.795 - 8.097]), managing household finances (OR = 1.897 [1.046 - 3.439]), attending more antenatal care visits (OR = 1.567 [1.163 - 2.112]), delivering more recently (OR = 1.438 [1.120 - 1.847] annually), and living closer to a health center (OR = 0.909 [0.846 - 0.976] per km) were independently associated with facility delivery. CONCLUSIONS: The strongest correlates of facility-based delivery in Bugesera District include previous delivery at a health facility, possession of health insurance, greater financial autonomy, more recent interactions with the health system, and proximity to a health center. Recent structural interventions in Rwanda, including the rapid scale-up of community-financed health insurance, likely contributed to the dramatic improvement in the health facility delivery rate observed in our study.

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An abstract of a thesis devoted to using helix-coil models to study unfolded states.\\

Research on polypeptide unfolded states has received much more attention in the last decade or so than it has in the past. Unfolded states are thought to be implicated in various

misfolding diseases and likely play crucial roles in protein folding equilibria and folding rates. Structural characterization of unfolded states has proven to be

much more difficult than the now well established practice of determining the structures of folded proteins. This is largely because many core assumptions underlying

folded structure determination methods are invalid for unfolded states. This has led to a dearth of knowledge concerning the nature of unfolded state conformational

distributions. While many aspects of unfolded state structure are not well known, there does exist a significant body of work stretching back half a century that

has been focused on structural characterization of marginally stable polypeptide systems. This body of work represents an extensive collection of experimental

data and biophysical models associated with describing helix-coil equilibria in polypeptide systems. Much of the work on unfolded states in the last decade has not been devoted

specifically to the improvement of our understanding of helix-coil equilibria, which arguably is the most well characterized of the various conformational equilibria

that likely contribute to unfolded state conformational distributions. This thesis seeks to provide a deeper investigation of helix-coil equilibria using modern

statistical data analysis and biophysical modeling techniques. The studies contained within seek to provide deeper insights and new perspectives on what we presumably

know very well about protein unfolded states. \\

Chapter 1 gives an overview of recent and historical work on studying protein unfolded states. The study of helix-coil equilibria is placed in the context

of the general field of unfolded state research and the basics of helix-coil models are introduced.\\

Chapter 2 introduces the newest incarnation of a sophisticated helix-coil model. State of the art modern statistical techniques are employed to estimate the energies

of various physical interactions that serve to influence helix-coil equilibria. A new Bayesian model selection approach is utilized to test many long-standing

hypotheses concerning the physical nature of the helix-coil transition. Some assumptions made in previous models are shown to be invalid and the new model

exhibits greatly improved predictive performance relative to its predecessor. \\

Chapter 3 introduces a new statistical model that can be used to interpret amide exchange measurements. As amide exchange can serve as a probe for residue-specific

properties of helix-coil ensembles, the new model provides a novel and robust method to use these types of measurements to characterize helix-coil ensembles experimentally

and test the position-specific predictions of helix-coil models. The statistical model is shown to perform exceedingly better than the most commonly used

method for interpreting amide exchange data. The estimates of the model obtained from amide exchange measurements on an example helical peptide

also show a remarkable consistency with the predictions of the helix-coil model. \\

Chapter 4 involves a study of helix-coil ensembles through the enumeration of helix-coil configurations. Aside from providing new insights into helix-coil ensembles,

this chapter also introduces a new method by which helix-coil models can be extended to calculate new types of observables. Future work on this approach could potentially

allow helix-coil models to move into use domains that were previously inaccessible and reserved for other types of unfolded state models that were introduced in chapter 1.

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Adrenergic receptors are prototypic models for the study of the relations between structure and function of G protein-coupled receptors. Each receptor is encoded by a distinct gene. These receptors are integral membrane proteins with several striking structural features. They consist of a single subunit containing seven stretches of 20-28 hydrophobic amino acids that represent potential membrane-spanning alpha-helixes. Many of these receptors share considerable amino acid sequence homology, particularly in the transmembrane domains. All of these macromolecules share other similarities that include one or more potential sites of extracellular N-linked glycosylation near the amino terminus and several potential sites of regulatory phosphorylation that are located intracellularly. By using a variety of techniques, it has been demonstrated that various regions of the receptor molecules are critical for different receptor functions. The seven transmembrane regions of the receptors appear to form a ligand-binding pocket. Cysteine residues in the extracellular domains may stabilize the ligand-binding pocket by participating in disulfide bonds. The cytoplasmic domains contain regions capable of interacting with G proteins and various kinases and are therefore important in such processes as signal transduction, receptor-G protein coupling, receptor sequestration, and down-regulation. Finally, regions of these macromolecules may undergo posttranslational modifications important in the regulation of receptor function. Our understanding of these complex relations is constantly evolving and much work remains to be done. Greater understanding of the basic mechanisms involved in G protein-coupled, receptor-mediated signal transduction may provide leads into the nature of certain pathophysiological states.

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The beta 1- and beta 2-adrenergic receptors are two structurally related, but pharmacologically distinguishable, receptor subtypes, both of which activate adenylyl cyclase in a catecholamine-dependent manner through the guanine nucleotide-binding regulatory protein Gs. The receptors are approximately 50% identical in amino acid sequence and each is characterized by the presence of seven putative transmembrane domains. To elucidate the structural basis for the pharmacological distinctions between these two receptor subtypes, we constructed a series of chimeric beta 1/beta 2-adrenergic receptor genes and expressed them by injection of RNA into Xenopus laevis oocytes. The pharmacological properties of the expressed chimeric receptor proteins were assessed by radioligand binding and adenylyl cyclase assays utilizing subtype-selective agonists and antagonists. Our data indicate that transmembrane region IV is largely responsible for determining beta 1 vs. beta 2 properties with respect to agonist binding (relative affinities for epinephrine and norepinephrine). Transmembrane regions VI and VII play an important role in determining binding of beta 1 vs. beta 2 selective antagonists. However, a number of the other transmembrane regions also contribute, to a lesser extent, to the determination of beta-adrenergic receptor subtype specificity for agonists and antagonists. Thus, several of the membrane-spanning regions appear to be involved in the determination of receptor subtype specificity, presumably by formation of a ligand-binding pocket, with determinants for agonist and antagonist binding being distinguishable.

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A shearing quotient (SQ) is a way of quantitatively representing the Phase I shearing edges on a molar tooth. Ordinary or phylogenetic least squares regression is fit to data on log molar length (independent variable) and log sum of measured shearing crests (dependent variable). The derived linear equation is used to generate an 'expected' shearing crest length from molar length of included individuals or taxa. Following conversion of all variables to real space, the expected value is subtracted from the observed value for each individual or taxon. The result is then divided by the expected value and multiplied by 100. SQs have long been the metric of choice for assessing dietary adaptations in fossil primates. Not all studies using SQ have used the same tooth position or crests, nor have all computed regression equations using the same approach. Here we focus on re-analyzing the data of one recent study to investigate the magnitude of effects of variation in 1) shearing crest inclusion, and 2) details of the regression setup. We assess the significance of these effects by the degree to which they improve or degrade the association between computed SQs and diet categories. Though altering regression parameters for SQ calculation has a visible effect on plots, numerous iterations of statistical analyses vary surprisingly little in the success of the resulting variables for assigning taxa to dietary preference. This is promising for the comparability of patterns (if not casewise values) in SQ between studies. We suggest that differences in apparent dietary fidelity of recent studies are attributable principally to tooth position examined.