Biogenesis of caveolae: a structural model for caveolin-induced domain formation

Caveolae are striking morphological features of the plasma membrane of mammalian cells. Caveolins, the major proteins of caveolae, play a crucial role in the formation of these invaginations of the plasma membrane; however, the precise mechanisms involved are only just starting to be unravelled. Recent studies suggest that caveolae are stable structures first generated in the Golgi complex. Their formation and exit from the Golgi complex is associated with caveolin oligomerisation, acquisition of detergent insolubility, and association with cholesterol. Modelling of caveolin-membrane interactions together with in vitro studies of caveolin peptides are providing new insights into how caveolin-lipid interactions could generate the unique architecture of the caveolar domain.

Assessment of the ability to model proteins with leucine-rich repeats in light of the latest structural information

The three-dimensional structures of leucine-rich repeat (LRR) -containing proteins from five different families were previously predicted based on the crystal structure of the ribonuclease inhibitor. using an approach that combined homology-based modeling, structure-based sequence alignment of LRRs, and several rational assumptions. The structural models have been produced based on very limited sequence similarity, which, in general. cannot yield trustworthy predictions. Recently, the protein structures from three of these five families have been determined. In this report we estimate the quality of the modeling approach by comparing the models with the experimentally determined structures. The comparison suggests that the general architecture, curvature, interior/exterior orientations of side chains. and backbone conformation of the LRR structures can be predicted correctly. On the other hand. the analysis revealed that, in some cases. it is difficult to predict correctly the twist of the overall super-helical structure. Taking into consideration the conclusions from these comparisons, we identified a new family of bacterial LRR proteins and present its structural model. The reliability of the LRR protein modeling suggests that it would be informative to apply similar modeling approaches to other classes of solenoid proteins.

The structural approach of a natrex model on equilibrium exchange rates

Following a general macroeconomic approach, this paper sets a closed micro-founded structural model to determine the long run real exchange rate of a developed economy. In particular, the analysis follows the structure of a Natrex model. The main contribution of this research paper is the development of a solid theoretical framework that analyse in depth the basis of the real exchange rate and the details of the equilibrium dynamics after any shock influencing the steady state. In our case, the intertemporal factors derived from the stock-flow relationship will be particularly determinant. The main results of the paper can be summarised as follows. In first place, a complete well-integrated structural model for long-run real exchange rate determination is developed from first principles. Moreover, within the concrete dynamics of the model, it is found that some convergence restrictions will be necessary. On one hand, for the medium run convergence the sensitivity of the trade balance to changes in real exchange rate should be higher that the correspondent one to the investment decisions. On the other hand, and regarding long-run convergence, it is also necessary both that there exists a negative relationship between investment and capital stock accumulation and that the global saving of the economy depends positively on net foreign debt accumulation. In addition, there are also interesting conclusions about the effects that certain shocks over the exogenous variables of the model have on real exchange rates.

The structural effects of divalent cations and insulin on phospholipid model membranes /

It is well accepted that structural studies with model membranes are of considerable value in understanding the structure of biological membranes. Many studies with models of pure phospholipids have been done; but the effects of divalent cations and protein on these models would make these studies more applicable to intact membrane. The present study, performed with above view, is a structural analysis of divalent io~cardio1ipin complexes using the technique of x-ray diffraction. Cardiolipin, precipitated from dilute solution by divalent ionscalcium, magnesium and barium, contains little water and the structure formed is similar to the structure of pure cardiolipin with low water content. The calcium-cardiolipin complex forms a pure hexagonal type II phase that exists from 40 to 400 C. The molar ratio of calcium and cardiolipin in the complex is 1 : 1. Cardiolipin, precipitated with magnesium and barium forms two co-existing phases, lamellar and hexagonal, the relative quantity of the two phases being dependent on temperature. The hexagonal phase type II consisting of water filled channels formed by adding calcium to cardiolipin may have a remarkable permeability property in intact membrane. Pure cardiolipin and insulin at pH 3.0 and 4.0 precipitate but form no organised structure. Lecithin/cardiolipin and insulin precipitated at pH 3.0 give a pure lamellar phase. As the lecithin/cardiolipin molar ratio changes from 93/7 to SO/50, (a) the repeat distance of the lamellar changes from 72.8 X to 68.2 A; (b) the amount of protein bound increases in such a way that cardiolipin/insulin molar ratio in the complex reaches a maximum constant value at lecithin/cardiolipin molar ratio 70/30. A structural model based on these data shows that the molecular arrangement of lipid and protein is a lipid bilayer coated with protein molecules. The lipid-protein interaction is chiefly electrostatic and little, if any, hydrophobic bonding occurs in this particular system. So, the proposed model is essentially the same as Davson-Daniellifs model of biological membrane.

Constructing a Structural Macroeconomic Model Using Multiple Techniques

This project constructs a structural model of the United States Economy. This task is tackled in two separate ways: first econometric methods and then using a neural network, both with a structure that mimics the structure of the U.S. economy. The structural model tracks the performance of U.S. GDP rather well in a dynamic simulation, with an average error of just over 1 percent. The neural network performed well, but suffered from some theoretical, as well as some implementation issues.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Robustness of corroded reinforced concrete structures. A structural performance approach

Structure and Infrastructure Engineering, 1-17

What explains the Great Moderation in the US? A structural analysis

This paper investigates what has caused output and inflation volatility to fall in the USusing a small scale structural model using Bayesian techniques and rolling samples. Thereare instabilities in the posterior of the parameters describing the private sector, the policyrule and the standard deviation of the shocks. Results are robust to the specification ofthe policy rule. Changes in the parameters describing the private sector are the largest,but those of the policy rule and the covariance matrix of the shocks explain the changes most.

Inflation dynamics: A structural econometric analysis

We develop and estimate a structural model of inflation that allowsfor a fraction of firms that use a backward looking rule to setprices. The model nests the purely forward looking New KeynesianPhillips curve as a particular case. We use measures of marginalcosts as the relevant determinant of inflation, as the theorysuggests, instead of an ad-hoc output gap. Real marginal costsare a significant and quantitatively important determinant ofinflation. Backward looking price setting, while statisticallysignificant, is not quantitatively important. Thus, we concludethat the New Keynesian Phillips curve provides a good firstapproximation to the dynamics of inflation.

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Motivational model of problem drinking for men and women /

This thesis tested a path model of the relationships of reasons for drinking and reasons for limiting drinking with consumption of alcohol and drinking problems. It was hypothesized that reasons for drinking would be composed of positively and negatively reinforcing reasons, and that reasons for limiting drinking would be composed of personal and social reasons. Problem drinking was operationalized as consisting of two factors, consumption and drinking problems, with a positive relationship between the two. It was predicted that positively and negatively reinforcing reasons for drinking would be associated with heavier consumption and, in turn, more drinking problems, through level of consumption. Negatively reinforcing reasons were also predicted to be associated with drinking problems directly, independent of level of consumption. It was hypothesized that reasons for limiting drinking would be associated with lower levels of consumption and would be related to fewer drinking problems, through level of consumption. Finally, among women, reasons for limiting drinking were expected to be associated with drinking problems directly, independent of level of consumption. The sample, was taken from the second phase of the Niagara Young Aduh Health Study, a community sample of young adult men and women. Measurement models of reasons for drinking, reasons for limiting drinking, and problem drinking were tested using Confirmatory Factor Analysis. After adequate fit of each measurement model was obtained, the complete structural model, with all hypothesized paths, was tested for goodness of fit. Cross-group equality constraints were imposed on all models to test for gender differences. The results provided evidence supporting the hypothesized structure of reasons for drinking and problem drinking. A single factor model of reasons for limiting drinking was used in the analyses because a two-factor model was inadequate. Support was obtained for the structural model. For example, the resuhs revealed independent influences of Positively Reinforcing Reasons for Drinking, Negatively Reinforcing Reasons for Drinking, and Reasons for Limiting Drinking on consumption. In addition. Negatively Reinforcing Reasons helped to account for Drinking Problems independent of the amount of alcohol consumed. Although an additional path from Reasons for Limiting Drinking to Drinking Problems was hypothesized for women, it was of marginal significance and did not improve the model's fit. As a result, no sex differences in the model were found. This may be a result of the convergence of drinking patterns for men and women. Furthermore, it is suggested that gender differences may only be found in clinical samples of problem drinkers, where the relative level of consumption for women and men is similar.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.