869 resultados para PROPORTIONAL HAZARD AND ACCELERATED FAILURE MODELS
Resumo:
It is nowadays recognized that the risk of human co-exposure to multiple mycotoxins is real. In the last years, a number of studies have approached the issue of co-exposure and the best way to develop a more precise and realistic assessment. Likewise, the growing concern about the combined effects of mycotoxins and their potential impact on human health has been reflected by the increasing number of toxicological studies on the combined toxicity of these compounds. Nevertheless, risk assessment of these toxins, still follows the conventional paradigm of single exposure and single effects, incorporating only the possibility of additivity but not taking into account the complex dynamics associated to interactions between different mycotoxins or between mycotoxins and other food contaminants. Considering that risk assessment is intimately related to the establishment of regulatory guidelines, once the risk assessment is completed, an effort to reduce or manage the risk should be followed to protect public health. Risk assessment of combined human exposure to multiple mycotoxins thus poses several challenges to scientists, risk assessors and risk managers and opens new avenues for research. This presentation aims to give an overview of the different challenges posed by the likelihood of human co-exposure to mycotoxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment and risk management. For this purpose, a physiologically-based framework that includes knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of multiple toxins is proposed. Regarding exposure assessment, the need of harmonized food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data and use of probabilistic models will be highlight, in order to develop a more precise and realistic exposure assessment. On the other hand, the application of predictive mathematical models to estimate mycotoxins’ combined effects from in vitro toxicity studies will be also discussed. Results from a recent Portuguese project aimed at exploring the toxic effects of mixtures of mycotoxins in infant foods and their potential health impact will be presented as a case study, illustrating the different aspects of risk assessment highlighted in this presentation. Further studies on hazard and exposure assessment of multiple mycotoxins, using harmonized approaches and methodologies, will be crucial towards an improvement in data quality and contributing to holistic risk assessment and risk management strategies for multiple mycotoxins in foodstuffs.
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This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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This dissertation provides a novel theory of securitization based on intermediaries minimizing the moral hazard that insiders can misuse assets held on-balance sheet. The model predicts how intermediaries finance different assets. Under deposit funding, the moral hazard is greatest for low-risk assets that yield sizable returns in bad states of nature; under securitization, it is greatest for high-risk assets that require high guarantees and large reserves. Intermediaries thus securitize low-risk assets. In an extension, I identify a novel channel through which government bailouts exacerbate the moral hazard and reduce total investment irrespective of the funding mode. This adverse effect is stronger under deposit funding, implying that intermediaries finance more risky assets off-balance sheet. The dissertation discusses the implications of different forms of guarantees. With explicit guarantees, banks securitize assets with either low information-intensity or low risk. By contrast, with implicit guarantees, banks only securitize assets with high information-intensity and low risk. Two extensions to the benchmark static and dynamic models are discussed. First, an extension to the static model studies the optimality of tranching versus securitization with guarantees. Tranching eliminates agency costs but worsens adverse selection, while securitization with guarantees does the opposite. When the quality of underlying assets in a certain security market is sufficiently heterogeneous, and when the highest quality assets are perceived to be sufficiently safe, securitization with guarantees dominates tranching. Second, in an extension to the dynamic setting, the moral hazard of misusing assets held on-balance sheet naturally gives rise to the moral hazard of weak ex-post monitoring in securitization. The use of guarantees reduces the dependence of banks' ex-post payoffs on monitoring efforts, thereby weakening monitoring incentives. The incentive to monitor under securitization with implicit guarantees is the weakest among all funding modes, as implicit guarantees allow banks to renege on their monitoring promises without being declared bankrupt and punished.
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This study presents the development and analysis of the psychometric properties of the Deviant Behavior Variety Scale (DBVS). Participants were 861 Portuguese adolescents (54 % female), aged between 12 and 19 years old. Two alternative models were tested using Confirmatory Factor Analysis. Although both models showed good fit indexes, the two-factor model didn’t presented discriminant validity. Further results provided evidence for the factorial and the convergent validity of the single-factor structure of the DVBS, which has also shown good internal consistency. Criterion validity was evaluated through the association with related variables, such as age and school failure, as well as the scale’s ability to capture group differences, namely between genders and school retentions, and finally by comparing a sub-group of convicted adolescents with a group of non-convicted ones regarding their engagement in delinquent activities. Overall, the scale presented good psychometric properties, with results supporting that the DBVS is a valid and reliable self-reported measure to evaluate adolescents’ involvement in deviance.
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Investigation of large, destructive earthquakes is challenged by their infrequent occurrence and the remote nature of geophysical observations. This thesis sheds light on the source processes of large earthquakes from two perspectives: robust and quantitative observational constraints through Bayesian inference for earthquake source models, and physical insights on the interconnections of seismic and aseismic fault behavior from elastodynamic modeling of earthquake ruptures and aseismic processes.
To constrain the shallow deformation during megathrust events, we develop semi-analytical and numerical Bayesian approaches to explore the maximum resolution of the tsunami data, with a focus on incorporating the uncertainty in the forward modeling. These methodologies are then applied to invert for the coseismic seafloor displacement field in the 2011 Mw 9.0 Tohoku-Oki earthquake using near-field tsunami waveforms and for the coseismic fault slip models in the 2010 Mw 8.8 Maule earthquake with complementary tsunami and geodetic observations. From posterior estimates of model parameters and their uncertainties, we are able to quantitatively constrain the near-trench profiles of seafloor displacement and fault slip. Similar characteristic patterns emerge during both events, featuring the peak of uplift near the edge of the accretionary wedge with a decay toward the trench axis, with implications for fault failure and tsunamigenic mechanisms of megathrust earthquakes.
To understand the behavior of earthquakes at the base of the seismogenic zone on continental strike-slip faults, we simulate the interactions of dynamic earthquake rupture, aseismic slip, and heterogeneity in rate-and-state fault models coupled with shear heating. Our study explains the long-standing enigma of seismic quiescence on major fault segments known to have hosted large earthquakes by deeper penetration of large earthquakes below the seismogenic zone, where mature faults have well-localized creeping extensions. This conclusion is supported by the simulated relationship between seismicity and large earthquakes as well as by observations from recent large events. We also use the modeling to connect the geodetic observables of fault locking with the behavior of seismicity in numerical models, investigating how a combination of interseismic geodetic and seismological estimates could constrain the locked-creeping transition of faults and potentially their co- and post-seismic behavior.
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Purpose: To investigate the pathogenesis of high fat diet (HFD)-induced hyperlipidemia (HLP) in mice, rats and hamsters and to comparatively evaluate their sensitivity to HFD. Methods: Mice, rats and hamsters were fed with high-fat diet formulation (HFD, n = 8) or a control diet (control, n = 8) for 4 weeks. Changes in body weight, relative liver weight, serum lipid profile, expressions of hepatic marker gene of lipid metabolism and liver morphology were observed in three hyperlipidemic models. Results: Elevated total cholesterol (TC), triglyceride, low density lipoprotein-cholesterol (LDL-C) and high density lipoprotein-cholesterol (HDL-C) levels and body weight were observed in all hyperlipidemic animals (p < 0.05), while hepatic steatosis was manifested in rat and hamster HLP models, and increased hepatic TC level was only seen (p < 0.05) in hamster HLP model. Suppression of HMG-CoA reductase and up-regulation of lipoproteinlipase were observed in all HFD groups. Hepatic gene expression of LDLR, CYP7A1, LCAT, SR-B1, and ApoA I, which are a response to reverse cholesterol transport (RCT), were inhibited by HFD in the three models. Among these models, simultaneous suppression of HMG-CR, LCAT, LDLR and SR-BI and elevated LPL were features of the hamster model. Conclusion: As the results show, impaired RCT and excessive fat accumulation are major contributors to pathogenesis of HFD-induced murine HLP. Thus, the hamster model is more appropriate for hyperlipidemia research.
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The purpose of this study was to examine the reliability and validity of the School Anxiety Inventory (SAI) using a sample of 646 Slovenian adolescents (48% boys), ranging in age from 12 to 19 years. Single confirmatory factor analyses replicated the correlated four-factor structure of scores on the SAI for anxiety-provoking school situations (Anxiety about School Failure and Punishment, Anxiety about Aggression, Anxiety about Social Evaluation, and Anxiety about Academic Evaluation), and the three-factor structure of the anxiety response systems (Physiological Anxiety, Cognitive Anxiety, and Behavioral Anxiety). Equality of factor structures was compared using multigroup confirmatory factor analyses. Measurement invariance for the four- and three-factor models was obtained across gender and school-level samples. The scores of the instrument showed high internal reliability and adequate test–retest reliability. The concurrent validity of the SAI scores was also examined through its relationship with the Social Anxiety Scale for Adolescents (SASA) scores and the Questionnaire about Interpersonal Difficulties for Adolescents (QIDA) scores. Correlations of the SAI scores with scores on the SASA and the QIDA were of low to moderate effect sizes.
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The International Space Station (ISS) requires a substantial amount of potable water for use by the crew. The economic and logistic limitations of transporting the vast amount of water required onboard the ISS necessitate onboard recovery and reuse of the aqueous waste streams. Various treatment technologies are employed within the ISS water processor to render the waste water potable, including filtration, ion exchange, adsorption, and catalytic wet oxidation. The ion exchange resins and adsorption media are combined in multifiltration beds for removal of ionic and organic compounds. A mathematical model (MFBMODEL™) designed to predict the performance of a multifiltration (MF) bed was developed. MFBMODEL consists of ion exchange models for describing the behavior of the different resin types in a MF bed (e.g., mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins) and an adsorption model capable of predicting the performance of the adsorbents in a MF bed. Multicomponent ion exchange ii equilibrium models that incorporate the water formation reaction, electroneutrality condition, and degree of ionization of weak acids and bases for mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins were developed and verified. The equilibrium models developed use a tanks-inseries approach that allows for consideration of variable influent concentrations. The adsorption modeling approach was developed in related studies and application within the MFBMODEL framework was demonstrated in the Appendix to this study. MFBMODEL consists of a graphical user interface programmed in Visual Basic and Fortran computational routines. This dissertation shows MF bed modeling results in which the model is verified for a surrogate of the ISS waste shower and handwash stream. In addition, a multicomponent ion exchange model that incorporates mass transfer effects was developed, which is capable of describing the performance of strong acid cation (SAC) and strong base anion (SBA) exchange resins, but not including reaction effects. This dissertation presents results showing the mass transfer model's capability to predict the performance of binary and multicomponent column data for SAC and SBA exchange resins. The ion exchange equilibrium and mass transfer models developed in this study are also applicable to terrestrial water treatment systems. They could be applied for removal of cations and anions from groundwater (e.g., hardness, nitrate, perchlorate) and from industrial process waters (e.g. boiler water, ultrapure water in the semiconductor industry).
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Intracochlear trauma from surgical insertion of bulky electrode arrays and inadequate pitch perception are areas of concern with current hand-assembled commercial cochlear implants. Parylene thin-film arrays with higher electrode densities and lower profiles are a potential solution, but lack rigidity and hence depend on manually fabricated permanently attached polyethylene terephthalate (PET) tubing based bulky backing devices. As a solution, we investigated a new backing device with two sub-systems. The first sub-system is a thin poly(lactic acid) (PLA) stiffener that will be embedded in the parylene array. The second sub-system is an attaching and detaching mechanism, utilizing a poly(N-vinylpyrrolidone)-block-poly(d,l-lactide) (PVP-b-PDLLA) copolymer-based biodegradable and water soluble adhesive, that will help to retract the PET insertion tool after implantation. As a proof-of-concept of sub-system one, a microfabrication process for patterning PLA stiffeners embedded in parylene has been developed. Conventional hotembossing, mechanical micromachining, and standard cleanroom processes were integrated for patterning fully released and discrete stiffeners coated with parylene. The released embedded stiffeners were thermoformed to demonstrate that imparting perimodiolar shapes to stiffener-embedded arrays will be possible. The developed process when integrated with the array fabrication process will allow fabrication of stiffener-embedded arrays in a single process. As a proof-of-concept of sub-system two, the feasibility of the attaching and detaching mechanism was demonstrated by adhering 1x and 1.5x scale PET tube-based insertion tools and PLA stiffeners embedded in parylene using the copolymer adhesive. The attached devices survived qualitative adhesion tests, thermoforming, and flexing. The viability of the detaching mechanism was tested by aging the assemblies in-vitro in phosphate buffer solution. The average detachment times, 2.6 minutes and 10 minutes for 1x and 1.5x scale devices respectively, were found to be clinically relevant with respect to the reported array insertion times during surgical implantation. Eventually, the stiffener-embedded arrays would not need to be permanently attached to current insertion tools which are left behind after implantation and congest the cochlear scala tympani chamber. Finally, a simulation-based approach for accelerated failure analysis of PLA stiffeners and characterization of PVP-b-PDLLA copolymer adhesive has been explored. The residual functional life of embedded PLA stiffeners exposed to body-fluid and thereby subjected to degradation and erosion has been estimated by simulating PLA stiffeners with different parylene coating failure types and different PLA types for a given parylene coating failure type. For characterizing the PVP-b-PDLLA copolymer adhesive, several formulations of the copolymer adhesive were simulated and compared based on the insertion tool detachment times that were predicted from the dissolution, degradation, and erosion behavior of the simulated adhesive formulations. Results indicate that the simulation-based approaches could be used to reduce the total number of time consuming and expensive in-vitro tests that must be conducted.
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BACKGROUND Eradication of bovine tuberculosis (bTB) through the application of test-and-cull programs is a declared goal of developed countries in which the disease is still endemic. Here, longitudinal data from more than 1,700 cattle herds tested during a 12 year-period in the eradication program in the region of Madrid, Spain, were analyzed to quantify the within-herd transmission coefficient (β) depending on the herd-type (beef/dairy/bullfighting). In addition, the probability to recover the officially bTB free (OTF) status in infected herds depending on the type of herd and the diagnostic strategy implemented was assessed using Cox proportional hazard models. RESULTS Overall, dairy herds showed higher β (median 4.7) than beef or bullfighting herds (2.3 and 2.2 respectively). Introduction of interferon-gamma (IFN-γ) as an ancillary test produced an apparent increase in the β coefficient regardless of production type, likely due to an increase in diagnostic sensitivity. Time to recover OTF status was also significantly lower in dairy herds, and length of bTB episodes was significantly reduced when the IFN-γ was implemented to manage the outbreak. CONCLUSIONS Our results suggest that bTB spreads more rapidly in dairy herds compared to other herd types, a likely cause being management and demographic-related factors. However, outbreaks in dairy herds can be controlled more rapidly than in typically extensive herd types. Finally, IFN-γ proved its usefulness to rapidly eradicate bTB at a herd-level.
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Urinary bladder cancer (UBC) is the second most frequent malignancy of the urinary system and the ninth most common cancer worldwide, affecting individuals over the age of 65. Several investigations have embarked on advancing knowledge of the mechanisms underlying urothelial carcinogenesis, understanding the mechanisms of antineoplastic drugs resistance and discovering new antineoplastic drugs. In vitro and in vivo models are crucial for providing additional insights into the mechanisms of urothelial carcinogenesis. With these models, various molecular pathways involved in urothelial carcinogenesis have been discovered, allowing therapeutic manipulation.
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Adjuvant-induced arthritis in rats is associated with growth failure, hypermetabolism and accelerated protein breakdown. The aim of this work was to study the effects of adjuvant-induced arthritis on GH and insulin-like growth factor-I (IGF-I). Arthritis was induced by an intradermal injection of complete Freund's adjuvant and rats were killed 18 and 22 days later. IGF-I and GH levels were measured by radioimmunoassay. Pituitary GH mRNA was analyzed by northern blot and IGF binding proteins (IGFBPs) by western blot. Arthritic rats showed a decrease in both serum and hepatic concentrations of IGF-I. On the contrary, arthritis increased the circulating IGFBPs. The serum concentration of IGF-I in the arthritic rats was negatively correlated with the body weight loss observed in these animals. Arthritis decreased the serum concentration of GH and this decrease seems to be due to an inhibition of GH synthesis, since pituitary GH mRNA content was decreased in arthritic rats (p<0.01). These data suggest that the decrease in body weight gain in arthritic rats may be, at least in part, secondary to the decrease in GH and IGF-I secretion. Furthermore, the increased serum IGFBPs may also be involved in the disease process.
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Marine protected areas (MPAs) are today's most important tools for the spatial management and conservation of marine species. Yet, the true protection that they provide to individual fish is unknown, leading to uncertainty associated with MPA effectiveness. In this study, conducted in a recently established coastal MPA in Portugal, we combined the results of individual home range estimation and population distribution models for 3 species of commercial importance and contrasting life histories to infer (1) the size of suitable areas where they would be fully protected and (2) the vulnerability to fishing mortality of each species. Results show that the relationship between MPA size and effective protection is strongly modulated by both the species' home range and the distribution of suitable habitat inside and outside the MPA. This approach provides a better insight into the true potential of MPAs in effectively protecting marine species, since it can reveal the size and location of the areas where protection is most effective and a clear, quantitative estimation of the vulnerability to fishing throughout an entire MPA.
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Cardiovascular diseases (CVDs) including, hypertension, coronary heart disease and heart failure are the leading cause of death worldwide. Hypertension, a chronic increase in blood pressure above 140/90 mmHg, is the single main contributor to deaths due to heart disease and stroke. In the heart, hypertension results in adaptive cardiac remodelling, including LV hypertrophy to normalize wall stress and maintain cardiac contractile function. However, chronic increases in BP results in the development of hypertensive heart disease (HHD). HHD describes the maladaptive changes during cardiac remodelling which result in reduced systolic and diastolic function and eventually heart failure. This includes ventricular dilation due to eccentric hypertrophy, cardiac fibrosis which stiffens the ventricular wall and microvascular rarefaction resulting in a decrease in coronary blood flow albeit an increase in energy demand. Chronic activation of the renin-angiotensin-system (RAS) with its effector peptide angiotensin (Ang)II plays a key role in the development of hypertension and the maladaptive changes in HHD. Ang II acts via the angiotensin type 1 receptor (AT1R) to mediate most of its pathological actions during HHD, including stimulation of cardiomyocyte hypertrophy, activation of cardiac fibroblasts and increased collagen deposition. The counter-regulatory axis of the RAS which is centred on the ACE2/Ang-(1-7)/Mas axis has been demonstrated to counteract the pathological actions of Ang II in the heart and vasculature. Ang-(1-7) via the Mas receptor prevents Ang II-induced cardiac hypertrophy and fibrosis and improves cardiac contractile function in animal models of HHD. In contrast, less is known about Ang-(1-9) although evidence has demonstrated that Ang-(1-9) also antagonises Ang II and is anti-hypertrophic and anti-fibrotic in animal models of acute cardiac remodelling. However, so far it is not well documented whether Ang-(1-9) can reverse established cardiac dysfunction and remodelling and whether it is beneficial when administered chronically. Therefore, the main aim of this thesis was to assess the effects of chronic Ang-(1-9) administration on cardiac structure and function in a model of Ang II-induced cardiac remodelling. Furthermore, this thesis aimed to investigate novel pathways contributing to the pathological remodelling in response to Ang II. First, a mouse model of chronic Ang II infusion was established and characterised by comparing the structural and functional effects of the infusion of a low and high dose of Ang II after 6 weeks. Echocardiographic measurements demonstrated that low dose Ang II infusion resulted in a gradual decline in cardiac function while a high dose of Ang II induced acute cardiac contractile dysfunction. Both doses equally induced the development of cardiac hypertrophy and cardiac fibrosis characterised by an increase in the deposition of collagen I and collagen III. Moreover, increases in gene expression of fibrotic and hypertrophic markers could be detected following high dose Ang II infusion over 6 weeks. Following this characterisation, the high dose infusion model was used to assess the effects of Ang-(1-9) on cardiac structural and functional remodelling in established disease. Initially, it was evaluated whether Ang-(1-9) can reverse Ang II-induced cardiac disease by administering Ang-(1-9) for 2-4 weeks following an initial 2 week infusion of a high dose of Ang II to induce cardiac contractile dysfunction. The infusion of Ang-(1-9) for 2 weeks was associated with a significant improvement of LV fractional shortening compared to Ang II infusion. However, after 4 weeks fractional shortening declined to Ang II levels. Despite the transient improvement in cardiac contractile function, Ang-(1-9) did not modulate blood pressure, LV hypertrophy or cardiac fibrosis. To further investigate the direct cardiac effects of Ang-(1-9), cardiac contractile performance in response to Ang-(1-9) was evaluated in the isolated Langendorff-perfused rat heart. Perfusion of Ang-(1-9) in the paced and spontaneously beating rat heart mediated a positive inotropic effect characterised by an increase in LV developed pressure, cardiac contractility and relaxation. This was in contrast to Ang II and Ang-(1-7). Furthermore, the positive inotropic effect to Ang-(1-9) was blocked by the AT1R antagonist losartan and the protein kinase A inhibitor H89. Next, endothelial-to-mesenchymal transition (EndMT) as a novel pathway that may contribute to Ang II-induced cardiac remodelling was assessed in Ang II-infused mice in vivo and in human coronary artery endothelial cells (HCAEC) in vitro. Infusion of Ang II to mice for 2-6 weeks resulted in a significant decrease in myocardial capillary density and this was associated with the occurrence of dual labelling of endothelial cells for endothelial and mesenchymal markers. In vitro stimulation of HCAEC with TGFβ and Ang II revealed that Ang II exacerbated TGF-induced gene expression of mesenchymal markers. This was not correlated with any changes in SMAD2 or ERK1/2 phosphorylation with co-stimulation of TGFβ and Ang II. However, superoxide production was significantly increased in HCAEC stimulated with Ang II but not TGFβ. Finally, the role of Ang II in microvesicle (MV)-mediated cardiomyocyte hypertrophy was investigated. MVs purified from neonatal rat cardiac fibroblasts were found to contain detectable Ang II and this was increased by stimulation of fibroblasts with Ang II. Treatment of cardiomyocytes with MVs derived from Ang II-stimulated fibroblasts induced cardiomyocyte hypertrophy which could be blocked by the AT1R antagonist losartan and an inhibitor of MV synthesis and release brefeldin A. Furthermore, Ang II was found to be present in MVs isolated from serum and plasma of Ang II-infused mice and SHRSP and WKY rats. Overall, the findings of this thesis demonstrate for the first time that the actions of Ang-(1-9) in cardiac pathology are dependent on its time of administration and that Ang-(1-9) can reverse Ang II-induced cardiac contractile dysfunction by acting as a positive inotrope. Furthermore, this thesis demonstrates evidence for an involvement of EndMT and MV signalling as novel pathways contributing to Ang II-induced cardiac fibrosis and hypertrophy, respectively. These findings provide incentive to further investigate the therapeutic potential of Ang-(1-9) in the treatment of cardiac contractile dysfunction in heart disease, establish the importance of novel pathways in Ang II-mediated cardiac remodelling and evaluate the significance of the presence of Ang II in plasma-derived MVs.