Statistical Multi-Objective Structural Damage Identification based on Dynamic Parameters

Evolutionary algorithms are suitable to solve damage identification problems in a multi-objective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this paper, a statistic structural damage detection method formulated in a multi-objective context is proposed. The statistic analysis is implemented to take into account the uncertainties existing in the structural model and measured structural modal parameters. The presented method is verified by a number of simulated damage scenarios. The effects of noise and damage levels on damage detection are investigated.

Comparison of the seismic behaviour between three building tests, all based on a two storey model house

Integral Masonry System consisting of intersecting steel trusses alo ng each of the three dimensional directions of space on walls and slabs using any masonry material, had yet been backed up by the previous adobe test for seismic areas. This paper presents the comparison this last test and the adaptation of the IMS using h ollow brick. A prototype based on a two storey model house (6mx6mx6m) has being also built in two different scales in order to maximize the load and size of the shake table: the first one half size the whole building (3mx3mx3m) and the second, a quarter of the real size (3mx3mx6m). Both tests have suffered some mild to moderate damages while supporting the higher seismic action subjected by the shake table, without even fissuring the first test and with very few damages the second one. The thickness of the hollow brick wall and the diameter of the tree - dimensional truss reinforcement were scaled to the real size test in order to ascertain its great structural behaviour in relation to the previous structural model calculations. The aim of this study is to sum marize the results of the research collaboration between the ETSAM - UPM and the PUCP in whose laboratory these tests were carried out.

Correlation of the structural and functional domains in the membrane protein Vpu from HIV-1

Vpu is an 81-residue membrane protein encoded by the HIV-1 genome. NMR experiments show that the protein folds into two distinct domains, a transmembrane hydrophobic helix and a cytoplasmic domain with two in-plane amphipathic α-helices separated by a linker region. Resonances in one-dimensional solid-state NMR spectra of uniformly 15N labeled Vpu are clearly segregated into two bands at chemical shift frequencies associated with NH bonds in a transmembrane α-helix, perpendicular to the membrane surface, and with NH bonds in the cytoplasmic helices parallel to the membrane surface. Solid-state NMR spectra of truncated Vpu2–51 (residues 2–51), which contains the transmembrane α-helix and the first amphipathic helix of the cytoplasmic domain, and of a construct Vpu28–81 (residues 28–81), which contains only the cytoplasmic domain, support this structural model of Vpu in the membrane. Full-length Vpu (residues 2–81) forms discrete ion-conducting channels of heterogeneous conductance in lipid bilayers. The most frequent conductances were 22 ± 3 pS and 12 ± 3 pS in 0.5 M KCl and 29 ± 3 pS and 12 ± 3 pS in 0.5 M NaCl. In agreement with the structural model, truncated Vpu2–51, which has the transmembrane helix, forms discrete channels in lipid bilayers, whereas the cytoplasmic domain Vpu28–81, which lacks the transmembrane helix, does not. This finding shows that the channel activity is associated with the transmembrane helical domain. The pattern of channel activity is characteristic of the self-assembly of conductive oligomers in the membrane and is compatible with the structural and functional findings.

Photoactive yellow protein: A structural prototype for the three-dimensional fold of the PAS domain superfamily

PAS domains are found in diverse proteins throughout all three kingdoms of life, where they apparently function in sensing and signal transduction. Although a wealth of useful sequence and functional information has become recently available, these data have not been integrated into a three-dimensional (3D) framework. The very early evolutionary development and diverse functions of PAS domains have made sequence analysis and modeling of this protein superfamily challenging. Limited sequence similarities between the ∼50-residue PAS repeats and one region of the bacterial blue-light photosensor photoactive yellow protein (PYP), for which ground-state and light-activated crystallographic structures have been determined to high resolution, originally were identified in sequence searches using consensus sequence probes from PAS-containing proteins. Here, we found that by changing a few residues particular to PYP function, the modified PYP sequence probe also could select PAS protein sequences. By mapping a typical ∼150-residue PAS domain sequence onto the entire crystallographic structure of PYP, we show that the PAS sequence similarities and differences are consistent with a shared 3D fold (the PAS/PYP module) with obvious potential for a ligand-binding cavity. Thus, PYP appears to prototypically exhibit all the major structural and functional features characteristic of the PAS domain superfamily: the shared PAS/PYP modular domain fold of ∼125–150 residues, a sensor function often linked to ligand or cofactor (chromophore) binding, and signal transduction capability governed by heterodimeric assembly (to the downstream partner of PYP). This 3D PAS/PYP module provides a structural model to guide experimental testing of hypotheses regarding ligand-binding, dimerization, and signal transduction.

An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies

As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.

A carbon activation model with application to longan seed char gasification

In this paper a new structural model is presented to describe the evolution of porosity of char during the gasification process. The model assumes the char structure to be composed of bundles of parallel graphite layers, and the reactivities of each layer with the gasification agent are assumed to be different to represent the different degree of heterogeneity of each layer (i.e. each layer will react with the gasification agent at a different rate). It is this difference in the reactivity that allows micropores to be created during the course of gasification. This simple structural model enables the evolution of pore volume, pore geometrical surface area and the pore size distribution to be described with respect to the extent of char burn-off. The model is tested against the experimental data of gasification of longan seed-derived char with carbon dioxide and it is found that the agreement between the model and the data is reasonably satisfactory, especially the evolution of surface area and pore volume with burn-off.

Essays on Microeconometrics

My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.

The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.

The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading

due to misclassification of unemployment.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.

Modelling and estimating models of physician labour supply and productivity

Ma thèse s’intéresse aux politiques de santé conçues pour encourager l’offre de services de santé. L’accessibilité aux services de santé est un problème majeur qui mine le système de santé de la plupart des pays industrialisés. Au Québec, le temps médian d’attente entre une recommandation du médecin généraliste et un rendez-vous avec un médecin spécialiste était de 7,3 semaines en 2012, contre 2,9 semaines en 1993, et ceci malgré l’augmentation du nombre de médecins sur cette même période. Pour les décideurs politiques observant l’augmentation du temps d’attente pour des soins de santé, il est important de comprendre la structure de l’offre de travail des médecins et comment celle-ci affecte l’offre des services de santé. Dans ce contexte, je considère deux principales politiques. En premier lieu, j’estime comment les médecins réagissent aux incitatifs monétaires et j’utilise les paramètres estimés pour examiner comment les politiques de compensation peuvent être utilisées pour déterminer l’offre de services de santé de court terme. En second lieu, j’examine comment la productivité des médecins est affectée par leur expérience, à travers le mécanisme du "learning-by-doing", et j’utilise les paramètres estimés pour trouver le nombre de médecins inexpérimentés que l’on doit recruter pour remplacer un médecin expérimenté qui va à la retraite afin de garder l’offre des services de santé constant. Ma thèse développe et applique des méthodes économique et statistique afin de mesurer la réaction des médecins face aux incitatifs monétaires et estimer leur profil de productivité (en mesurant la variation de la productivité des médecins tout le long de leur carrière) en utilisant à la fois des données de panel sur les médecins québécois, provenant d’enquêtes et de l’administration. Les données contiennent des informations sur l’offre de travail de chaque médecin, les différents types de services offerts ainsi que leurs prix. Ces données couvrent une période pendant laquelle le gouvernement du Québec a changé les prix relatifs des services de santé. J’ai utilisé une approche basée sur la modélisation pour développer et estimer un modèle structurel d’offre de travail en permettant au médecin d’être multitâche. Dans mon modèle les médecins choisissent le nombre d’heures travaillées ainsi que l’allocation de ces heures à travers les différents services offerts, de plus les prix des services leurs sont imposés par le gouvernement. Le modèle génère une équation de revenu qui dépend des heures travaillées et d’un indice de prix représentant le rendement marginal des heures travaillées lorsque celles-ci sont allouées de façon optimale à travers les différents services. L’indice de prix dépend des prix des services offerts et des paramètres de la technologie de production des services qui déterminent comment les médecins réagissent aux changements des prix relatifs. J’ai appliqué le modèle aux données de panel sur la rémunération des médecins au Québec fusionnées à celles sur l’utilisation du temps de ces mêmes médecins. J’utilise le modèle pour examiner deux dimensions de l’offre des services de santé. En premierlieu, j’analyse l’utilisation des incitatifs monétaires pour amener les médecins à modifier leur production des différents services. Bien que les études antérieures ont souvent cherché à comparer le comportement des médecins à travers les différents systèmes de compensation,il y a relativement peu d’informations sur comment les médecins réagissent aux changementsdes prix des services de santé. Des débats actuels dans les milieux de politiques de santé au Canada se sont intéressés à l’importance des effets de revenu dans la détermination de la réponse des médecins face à l’augmentation des prix des services de santé. Mon travail contribue à alimenter ce débat en identifiant et en estimant les effets de substitution et de revenu résultant des changements des prix relatifs des services de santé. En second lieu, j’analyse comment l’expérience affecte la productivité des médecins. Cela a une importante implication sur le recrutement des médecins afin de satisfaire la demande croissante due à une population vieillissante, en particulier lorsque les médecins les plus expérimentés (les plus productifs) vont à la retraite. Dans le premier essai, j’ai estimé la fonction de revenu conditionnellement aux heures travaillées, en utilisant la méthode des variables instrumentales afin de contrôler pour une éventuelle endogeneité des heures travaillées. Comme instruments j’ai utilisé les variables indicatrices des âges des médecins, le taux marginal de taxation, le rendement sur le marché boursier, le carré et le cube de ce rendement. Je montre que cela donne la borne inférieure de l’élasticité-prix direct, permettant ainsi de tester si les médecins réagissent aux incitatifs monétaires. Les résultats montrent que les bornes inférieures des élasticités-prix de l’offre de services sont significativement positives, suggérant que les médecins répondent aux incitatifs. Un changement des prix relatifs conduit les médecins à allouer plus d’heures de travail au service dont le prix a augmenté. Dans le deuxième essai, j’estime le modèle en entier, de façon inconditionnelle aux heures travaillées, en analysant les variations des heures travaillées par les médecins, le volume des services offerts et le revenu des médecins. Pour ce faire, j’ai utilisé l’estimateur de la méthode des moments simulés. Les résultats montrent que les élasticités-prix direct de substitution sont élevées et significativement positives, représentant une tendance des médecins à accroitre le volume du service dont le prix a connu la plus forte augmentation. Les élasticitésprix croisées de substitution sont également élevées mais négatives. Par ailleurs, il existe un effet de revenu associé à l’augmentation des tarifs. J’ai utilisé les paramètres estimés du modèle structurel pour simuler une hausse générale de prix des services de 32%. Les résultats montrent que les médecins devraient réduire le nombre total d’heures travaillées (élasticité moyenne de -0,02) ainsi que les heures cliniques travaillées (élasticité moyenne de -0.07). Ils devraient aussi réduire le volume de services offerts (élasticité moyenne de -0.05). Troisièmement, j’ai exploité le lien naturel existant entre le revenu d’un médecin payé à l’acte et sa productivité afin d’établir le profil de productivité des médecins. Pour ce faire, j’ai modifié la spécification du modèle pour prendre en compte la relation entre la productivité d’un médecin et son expérience. J’estime l’équation de revenu en utilisant des données de panel asymétrique et en corrigeant le caractère non-aléatoire des observations manquantes à l’aide d’un modèle de sélection. Les résultats suggèrent que le profil de productivité est une fonction croissante et concave de l’expérience. Par ailleurs, ce profil est robuste à l’utilisation de l’expérience effective (la quantité de service produit) comme variable de contrôle et aussi à la suppression d’hypothèse paramétrique. De plus, si l’expérience du médecin augmente d’une année, il augmente la production de services de 1003 dollar CAN. J’ai utilisé les paramètres estimés du modèle pour calculer le ratio de remplacement : le nombre de médecins inexpérimentés qu’il faut pour remplacer un médecin expérimenté. Ce ratio de remplacement est de 1,2.

Analyzing change in medication use - statistical approaches

The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.

ESSAYS IN ENERGY, ENVIRONMENT AND TECHNOLOGICAL CHANGE

This dissertation studies technological change in the context of energy and environmental economics. Technology plays a key role in reducing greenhouse gas emissions from the transportation sector. Chapter 1 estimates a structural model of the car industry that allows for endogenous product characteristics to investigate how gasoline taxes, R&D subsidies and competition affect fuel efficiency and vehicle prices in the medium-run, both through car-makers' decisions to adopt technologies and through their investments in knowledge capital. I use technology adoption and automotive patents data for 1986-2006 to estimate this model. I show that 92% of fuel efficiency improvements between 1986 and 2006 were driven by technology adoption, while the role of knowledge capital is largely to reduce the marginal production costs of fuel-efficient cars. A counterfactual predicts that an additional $1/gallon gasoline tax in 2006 would have increased the technology adoption rate, and raised average fuel efficiency by 0.47 miles/gallon, twice the annual fuel efficiency improvement in 2003-2006. An R&D subsidy that would reduce the marginal cost of knowledge capital by 25% in 2006 would have raised investment in knowledge capital. This subsidy would have raised fuel efficiency only by 0.06 miles/gallon in 2006, but would have increased variable profits by $2.3 billion over all firms that year. Passenger vehicle fuel economy standards in the United States will require substantial improvements in new vehicle fuel economy over the next decade. Economic theory suggests that vehicle manufacturers adopt greater fuel-saving technologies for vehicles with larger market size. Chapter 2 documents a strong connection between market size, measured by sales, and technology adoption. Using variation consumer demographics and purchasing pattern to account for the endogeneity of market size, we find that a 10 percent increase in market size raises vehicle fuel efficiency by 0.3 percent, as compared to a mean improvement of 1.4 percent per year over 1997-2013. Historically, fuel price and demographic-driven market size changes have had large effects on technology adoption. Furthermore, fuel taxes would induce firms to adopt fuel-saving technologies on their most efficient cars, thereby polarizing the fuel efficiency distribution of the new vehicle fleet.

The bacterial helicase-primase interaction: a common structural/functional module

The lack of a high-resolution structure for the bacterial helicase-primase complex and the fragmented structural information for the individual proteins have been hindering our detailed understanding of this crucial binary protein interaction. Two new structures for the helicase-interacting domain of the bacterial primases from Escherichia coli and Bacillus stearothermophilus have recently been solved and both revealed a unique and surprising structural similarity to the amino-terminal domain of the helicase itself. In this minireview, the current data are discussed and important new structural and functional aspects of the helicase-primase interaction are highlighted. An attractive structural model with direct biological significance for the function of this complex and also for the development of new antibacterial compounds is examined.

SOVLENT REACTIVITY AND INTERFACE EVOLUTION AT MODEL ELECTRODES FOR ENERGY APPLICATIONS

The Li-ion rechargeable battery (LIB) is widely used as an energy storage device, but has significant limitations in battery cycle life and safety. During initial charging, decomposition of the ethylene carbonate (EC)-based electrolytes of the LIB leads to the formation of a passivating layer on the anode known as the solid electrolyte interphase (SEI). The formation of an SEI has great impact on the cycle life and safety of LIB, yet mechanistic aspects of SEI formation are not fully understood. In this dissertation, two surface science model systems have been created under ultra-high vacuum (UHV) to probe the very initial stage of SEI formation at the model carbon anode surfaces of LIB. The first model system, Model System I, is an lithium-carbonate electrolyte/graphite C(0001) system. I have developed a temperature programmed desorption/temperature programmed reaction spectroscopy (TPD/TPRS) instrument as part of my dissertation to study Model System I in quantitative detail. The binding strengths and film growth mechanisms of key electrolyte molecules on model carbon anode surfaces with varying extents of lithiation were measured by TPD. TPRS was further used to track the gases evolved from different reduction products in the early-stage SEI formation. The branching ratio of multiple reaction pathways was quantified for the first time and determined to be 70.% organolithium products vs. 30% inorganic lithium product. The obtained branching ratio provides important information on the distribution of lithium salts that form at the very onset of SEI formation. One of the key reduction products formed from EC in early-stage SEI formation is lithium ethylene dicarbonate (LEDC). Despite intensive studies, the LEDC structure in either the bulk or thin-film (SEI) form is unknown. To enable structural study, pure LEDC was synthesized and subject to synchrotron X-ray diffraction measurements (bulk material) and STM measurements (deposited films). To enable studies of LEDC thin films, Model System II, a lithium ethylene dicarbonate (LEDC)-dimethylformamide (DMF)/Ag(111) system was created by a solution microaerosol deposition technique. Produced films were then imaged by ultra-high vacuum scanning tunneling microscopy (UHV-STM). As a control, the dimethylformamide (DMF)-Ag(111) system was first prepared and its complex 2D phase behavior was mapped out as a function of coverage. The evolution of three distinct monolayer phases of DMF was observed with increasing surface pressure — a 2D gas phase, an ordered DMF phase, and an ordered Ag(DMF)2 complex phase. The addition of LEDC to this mixture, seeded the nucleation of the ordered DMF islands at lower surface pressures (DMF coverages), and was interpreted through nucleation theory. A structural model of the nucleation seed was proposed, and the implication of ionic SEI products, such as LEDC, in early-stage SEI formation was discussed.

Nonlinear modelling of non-structural masonry walls under a low-intensity earthquake motion: calibration through a parametric study

This thesis aims to understand the behavior of a low-rise unreinforced masonry building (URM), the typical residential house in the Netherlands, when subjected to low-intensity earthquakes. In fact, in the last decades, the Groningen region was hit by several shallow earthquakes caused by the extraction of natural gas. In particular, the focus is addressed to the internal non-structural walls and to their interaction with the structural parts of the building. A simple and cost-efficient 2D FEM model is developed, focused on the interfaces representing mortar layers that are present between the non-structural walls and the rest of the structure. As a reference for geometries and materials, it has been taken into consideration a prototype that was built in full-scale at the EUCENTRE laboratory of Pavia (Italy). Firstly, a quasi-static analysis is performed by gradually applying a prescribed displacement on the roof floor of the structure. Sensitivity analyses are conducted on some key parameters characterizing mortar. This analysis allows for the calibration of their values and the evaluation of the reliability of the model. Successively, a transient analysis is performed to effectively subject the model to a seismic action and hence also evaluate the mechanical response of the building over time. Moreover, it was possible to compare the results of this analysis with the displacements recorded in the experimental tests by creating a model representing the entire considered structure. As a result, some conditions for the model calibration are defined. The reliability of the model is then confirmed by both the reasonable results obtained from the sensitivity analysis and the compatibility of the values obtained for the top displacement of the roof floor of the experimental test, and the same value acquired from the structural model.

Oligomerization, Membrane Association, And In Vivo Phosphorylation Of Sugarcane Udp-glucose Pyrophosphorylase.

Sugarcane is a monocot plant that accumulates sucrose to levels of up to 50% of dry weight in the stalk. The mechanisms that are involved in sucrose accumulation in sugarcane are not well understood, and little is known with regard to factors that control the extent of sucrose storage in the stalks. UDP-glucose pyrophosphorylase (UGPase; EC 2.7.7.9) is an enzyme that produces UDP-glucose, a key precursor for sucrose metabolism and cell wall biosynthesis. The objective of this work was to gain insights into the ScUGPase-1 expression pattern and regulatory mechanisms that control protein activity. ScUGPase-1 expression was negatively correlated with the sucrose content in the internodes during development, and only slight differences in the expression patterns were observed between two cultivars that differ in sucrose content. The intracellular localization of ScUGPase-1 indicated partial membrane association of this soluble protein in both the leaves and internodes. Using a phospho-specific antibody, we observed that ScUGPase-1 was phosphorylated in vivo at the Ser-419 site in the soluble and membrane fractions from the leaves but not from the internodes. The purified recombinant enzyme was kinetically characterized in the direction of UDP-glucose formation, and the enzyme activity was affected by redox modification. Preincubation with H2O2 strongly inhibited this activity, which could be reversed by DTT. Small angle x-ray scattering analysis indicated that the dimer interface is located at the C terminus and provided the first structural model of the dimer of sugarcane UGPase in solution.