Effects of single-dose atorvastatin on interleukin-6, interferon gamma, and myocardial no-reflow in a rabbit model of acute myocardial infarction and reperfusion

The mechanisms of statins relieving the no-reflow phenomenon and the effects of single-dose statins on it are not well known. This study sought to investigate the effects of inflammation on the no-reflow phenomenon in a rabbit model of acute myocardial infarction and reperfusion (AMI/R) and to evaluate the effects of single-dose atorvastatin on inflammation and myocardial no-reflow. Twenty-four New Zealand white male rabbits (5-6 months old) were randomized to three groups of eight: a sham-operated group, an AMI/R group, and an atorvastatin-treated group (10 mg/kg). Animals in the latter two groups were subjected to 4 h of coronary occlusion followed by 2 h of reperfusion. Serum levels of interleukin (IL)-6 were measured by enzyme-linked immunosorbent assay. The expression of interferon gamma (IFN-γ) in normal and infarcted (reflow and no-reflow) myocardial tissue was determined by immunohistochemical methods. The area of no-reflow and necrosis was evaluated pathologically. Levels of serum IL-6 were significantly lower in the atorvastatin group than in the AMI/R group (P<0.01). Expression of IFN-γ in infarcted reflow and no-reflow myocardial tissue was also significantly lower in the atorvastatin group than in the AMI/R group. The mean area of no-reflow [47.01% of ligation area (LA)] was significantly smaller in the atorvastatin group than in the AMI/R group (85.67% of LA; P<0.01). The necrosis area was also significantly smaller in the atorvastatin group (85.94% of LA) than in the AMI/R group (96.56% of LA; P<0.01). In a secondary analysis, rabbits in the atorvastatin and AMI/R groups were divided into two groups based on necrosis area (90% of LA): a small group (<90% of LA) and a large group (>90% of LA). There was no significant difference in the area of no-reflow between the small (61.40% of LA) and large groups (69.87% of LA; P>0.05). Single-dose atorvastatin protected against inflammation and myocardial no-reflow and reduced infarct size during AMI/R in rabbits. No-reflow was not dependent on the reduction of infarct size.

Putative role of ischemic postconditioning in a rat model of limb ischemia and reperfusion: involvement of hypoxia-inducible factor-1α expression

Hypoxia-inducible factor-1α (HIF-1α) is one of the most potent angiogenic growth factors. It improves angiogenesis and tissue perfusion in ischemic skeletal muscle. In the present study, we tested the hypothesis that ischemic postconditioning is effective for salvaging ischemic skeletal muscle resulting from limb ischemia-reperfusion injury, and that the mechanism involves expression of HIF-1α. Wistar rats were randomly divided into three groups (n=36 each): sham-operated (group S), hindlimb ischemia-reperfusion (group IR), and ischemic postconditioning (group IPO). Each group was divided into subgroups (n=6) according to reperfusion time: immediate (0 h, T0), 1 h (T1), 3 h (T3), 6 h (T6), 12 h (T12), and 24 h (T24). In the IPO group, three cycles of 30-s reperfusion and 30-s femoral aortic reocclusion were carried out before reperfusion. At all reperfusion times (T0-T24), serum creatine kinase (CK) and lactate dehydrogenase (LDH) activities, as well as interleukin (IL)-6, IL-10, and tumor necrosis factor-α (TNF-α) concentrations, were measured in rats after they were killed. Histological and immunohistochemical methods were used to assess the skeletal muscle damage and HIF-1α expression in skeletal muscle ischemia. In groups IR and IPO, serum LDH and CK activities and TNF-α, IL-6, and IL-10 concentrations were all significantly increased compared to group S, and HIF-1α expression was up-regulated (P<0.05 or P<0.01). In group IPO, serum LDH and CK activities and TNF-α and IL-6 concentrations were significantly decreased, IL-10 concentration was increased, HlF-1α expression was down-regulated (P<0.05 or P<0.01), and the pathological changes were reduced compared to group IR. The present study suggests that ischemic postconditioning can reduce skeletal muscle damage caused by limb ischemia-reperfusion and that its mechanisms may be related to the involvement of HlF-1α in the limb ischemia-reperfusion injury-triggered inflammatory response.

Protective effects of tumor necrosis factor-α blockade by adalimumab on articular cartilage and subchondral bone in a rat model of osteoarthritis

We aimed to investigate the effects of an anti-tumor necrosis factor-α antibody (ATNF) on cartilage and subchondral bone in a rat model of osteoarthritis. Twenty-four rats were randomly divided into three groups: sham-operated group (n=8); anterior cruciate ligament transection (ACLT)+normal saline (NS) group (n=8); and ACLT+ATNF group (n=8). The rats in the ACLT+ATNF group received subcutaneous injections of ATNF (20 μg/kg) for 12 weeks, while those in the ACLT+NS group received NS at the same dose for 12 weeks. All rats were euthanized at 12 weeks after surgery and specimens from the affected knees were harvested. Hematoxylin and eosin staining, Masson's trichrome staining, and Mankin score assessment were carried out to evaluate the cartilage status and cartilage matrix degradation. Matrix metalloproteinase (MMP)-13 immunohistochemistry was performed to assess the cartilage molecular metabolism. Bone histomorphometry was used to observe the subchondral trabecular microstructure. Compared with the rats in the ACLT+NS group, histological and Mankin score analyses showed that ATNF treatment reduced the severity of the cartilage lesions and led to a lower Mankin score. Immunohistochemical and histomorphometric analyses revealed that ATNF treatment reduced the ACLT-induced destruction of the subchondral trabecular microstructure, and decreased MMP-13 expression. ATNF treatment may delay degradation of the extracellular matrix via a decrease in MMP-13 expression. ATNF treatment probably protects articular cartilage by improving the structure of the subchondral bone and reducing the degradation of the cartilage matrix.

Calculation of viscoelastic properties of edible films: application of three models

The viscoelastic properties of edible films can provide information at the structural level of the biopolymers used. The objective of this work was to test three simple models of linear viscoelastic theory (Maxwell, Generalized Maxwell with two units in parallel, and Burgers) using the results of stress relaxation tests in edible films of myofibrillar proteins of Nile Tilapia. The films were elaborated according to a casting technique and pre-conditioned at 58% relative humidity and 22ºC for 4 days. The testing sample (15mm x 118mm) was submitted to tests of stress relaxation in an equipment of physical measurements, TA.XT2i. The deformation, imposed to the sample, was 1%, guaranteeing the permanency in the domain of the linear viscoelasticity. The models were fitted to experimental data (stress x time) by nonlinear regression. The Generalized Maxwell model with two units in parallel and the Burgers model represented the relaxation curves of stress satisfactorily. The viscoelastic properties varied in a way that they were less dependent on the thickness of the films.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Ball Bearing Model Performance on Various Sized Rotors with and without Centrifugal and Gyroscopic Forces

Bearing performance signi cantly a ects the dynamic behaviors and estimated working life of a rotating system. A common bearing type is the ball bearing, which has been under investigation in numerous published studies. The complexity of the ball bearing models described in the literature varies. Naturally, model complexity is related to computational burden. In particular, the inclusion of centrifugal forces and gyroscopic moments signi cantly increases the system degrees of freedom and lengthens solution time. On the other hand, for low or moderate rotating speeds, these e ects can be neglected without signi cant loss of accuracy. The objective of this paper is to present guidelines for the appropriate selection of a suitable bearing model for three case studies. To this end, two ball bearing models were implemented. One considers high-speed forces, and the other neglects them. Both models were used to study a three structures, and the simulation results were.

Application of the Hsu model to soybean grain hydration

A comparative analysis of the theoretical-experimental study, developed by Hsu on the hydration of Amsoy 71 soybean grain, was performed through several soaking experiments using CD 202 soybean at 10, 20, 30, 40, and 50 °C, measuring moisture content over time. The results showed that CD 202 soybean equilibrium moisture content, Xeq, does not depend on temperature and is 21% higher than that found by Hsu, suggesting that soybean cultivar exerts great influence on Xeq. The Hsu model was numerically solved and its parameters were adjusted by the least squares method, with maximum deviations of +/- 10% relative to the experimental values. The limiting step in the mass transfer process during hydration corresponds to water diffusion inside the grain, leading to radial moisture gradients that decrease over time and with an increase in temperature. Regardless of the soybean cultivar, diffusivity increases as temperature or moisture content increases. However, the values of this transport property for Amsoy 71 were superior to those of CD 202, very close at the beginning of hydration at 20 °C and almost three times higher at the end of hydration at 50 °C.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Finnish perceptions on management accounting systems: towards an upgraded sophistication model

This study is based on a large survey study of over 1500 Finnish companies’ usage, needs and implementation difficulties of management accounting systems. The study uses quantitative, qualitative and mixed methods to answer the research questions. The empirical data used in the study was gathered through structured interviews with randomly selected companies of varying sizes and industries. The study answers the three research questions by analyzing the characteristics and behaviors of companies working in Finland. The study found five distinctive groups of companies according to the characteristics of their cost information and management accounting system use. The study also showed that the state of cost information and management accounting systems depends on the industry and size of the companies. It was found that over 50% of the companies either did not know how their systems could be updated or saw systems as inadequate. The qualitative side also highlighted the needs for tailored and integrated management accounting systems for creating more value to the managers of companies. The major inhibitors of new system implementation were the lack of both monetary and human resources. Through the use of mixed methods and design science a new and improved sophistication model is created based on previous research results combined with the information gathered from previous literature. The sophistication model shows the different stages of management accounting systems in use and what companies can achieve with the implementation and upgrading of their systems.

Effects of algal turbidity on foraging and antipredator behaviour of the three-spined stickleback (Gasterosteus aculeatus)

The aim of this thesis was to examine how aquatic organisms, such as fish, behave in an altered environmental condition. Many species of fish use vision as their primary tool to gain information about their surrounding environment. The visual conditions of aquatic habitats are often altered as a result of anthropogenic disturbance, such as eutrophication that initiates algal turbidity. In general, turbidity reduces the visibility and can be hypothesized to have an influence on the behaviour of fish. I used the three-spined stickleback (Gasterosteus aculeatus) as a model species and conducted four studies in the laboratory to test how algal turbidity affects its behaviour. In this thesis, two major behavioural aspects are discussed. The first is antipredator behaviour. In study I, the combined effects of turbidity and shoot density on habitat choice (shelter vs open) behaviour was tested on a group of sticklebacks (20 fish) in the presence and absence of piscivorous perch (Perca fluviatilis). In study II, I examined the behavioural responses of feeding sticklebacks when they were exposed to the sudden appearance of an avian predator (the silhouette of a common tern, Sterna hirundo). The study was done in turbid and clear water using three different groups sizes (1, 3 and 6 fish). The second aspect is foraging behaviour. Study III & IV focused on the effects of algal turbidity on the foraging performance of sticklebacks. In study III, I conducted two separate experiments to examine the effects of turbidity on prey consumption and prey choice of sticklebacks. In this experiment turbidity levels and the proportion of large and small prey (Daphnia spp.) were manipulated. In study IV, I studied whether a group of six sticklebacks can distribute themselves according to food input at two feeding stations in a way that provided each fish with the same amount of food in clear and turbid water. I also observed whether the fish can follow changes in resource distribution between the foraging patches. My results indicate an overall influence of algal turbidity on the antipredator and foraging behaviour of sticklebacks. In the presence of a potential predator, the use of the sheltered habitat was more pronounced at higher turbidity. Besides this, sticklebacks reduced their activity levels with predator presence at higher turbidity and shoot density levels, suggesting a possible antipredator adaptation to avoid a predator. When exposed to a sudden appearance of an avian predator, sticklebacks showed a weaker antipredator response in turbid water, which suggests that turbidity degrades the risk assessment capabilities of sticklebacks. I found an effect of group size but not turbidity in the proportion of sticklebacks that fled to the shelter area, which indicates that sticklebacks are able to communicate among group members at the experimental turbidity levels. I found an overall negative effect of turbidity on food intake. Both turbidity and changes in the proportion of prey sizes played a significant role in a stickleback’s prey selection. At lower turbidity levels (clear <1 and 5 NTU) sticklebacks showed preferences for large prey, whereas in more turbid conditions and when the proportion of large to small prey increased sticklebacks became increasingly random in their prey selection. Finally, my results showed that groups of sticklebacks disperse themselves between feeding stations according to the reward ratios following the predictions of the ideal free distribution theory. However, they took a significantly longer time to reach the equilibrium distribution in turbid water than in clear water. In addition, they showed a slower response to changes in resource distribution in a turbid environment. These findings suggest that turbidity interferes with the information transfer among group foragers. It is important to understand that aquatic animals are often exposed to a degraded environment. The findings of this thesis suggest that algal turbidity negatively affects their behavioural performance. The results also shed light on the underlying behavioural strategies of sticklebacks in turbid conditions that might help them adapt to an altered environmental situation and increase their survival. In conclusion, I hold that although algal turbidity has detrimental effects on the antipredator and foraging behaviour of sticklebacks, their behavioural adjustment might help them adapt to a changing environment.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Calculation of the magnetic field penetration depth for high-Tc cuprate superconductors based on the Interlayer Pair Tunneling model /

In this work, the magnetic field penetration depth for high-Tc cuprate superconductors is calculated using a recent Interlayer Pair Tunneling (ILPT) model proposed by Chakravarty, Sudb0, Anderson, and Strong [1] to explain high temperature superconductivity. This model involves a "hopping" of Cooper pairs between layers of the unit cell which acts to amplify the pairing mechanism within the planes themselves. Recent work has shown that this model can account reasonably well for the isotope effect and the dependence of Tc on nonmagnetic in-plane impurities [2] , as well as the Knight shift curves [3] and the presence of a magnetic peak in the neutron scattering intensity [4]. In the latter case, Yin et al. emphasize that the pair tunneling must be the dominant pairing mechanism in the high-Tc cuprates in order to capture the features found in experiments. The goal of this work is to determine whether or not the ILPT model can account for the experimental observations of the magnetic field penetration depth in YBa2Cu307_a7. Calculations are performed in the weak and strong coupling limits, and the efi"ects of both small and large strengths of interlayer pair tunneling are investigated. Furthermore, as a follow up to the penetration depth calculations, both the neutron scattering intensity and the Knight shift are calculated within the ILPT formalism. The aim is to determine if the ILPT model can yield results consistent with experiments performed for these properties. The results for all three thermodynamic properties considered are not consistent with the notion that the interlayer pair tunneling must be the dominate pairing mechanism in these high-Tc cuprate superconductors. Instead, it is found that reasonable agreement with experiments is obtained for small strengths of pair tunneling, and that large pair tunneling yields results which do not resemble those of the experiments.

Sedimentology and taphonomy of storm-generated shell beds from the Verulam formation (Ordovician), Lakefield and Gamebridge quarries, Southern Ontario, Canada /

The Verulam Formation (Middle Ordovician) at the Lakefield Quarry and Gamebridge Quarry, southern Ontario, is comprised of five main lithofacies. These include shoal deposits consisting of Lithofacies 1, winnowed crinoidal grainstones and, shelf deposits consisting of: Lithofacies 2, wackestones, packstones, grainstones, and rudstones; Lithofacies 3, laminated calcisiltites; Lithofacies 4, nodular wackestones and mudstones; and, Lithofacies 5, laminated mudstones and shales. The distribution of the lithofacies was influenced by variations in storm frequency and intensity during a relative sea level fall. Predominant convex-up attitudes of concavo-convex shells within shell beds suggest syndepositional reworking during storm events. The bimodal orientations of shell axes on the upper surfaces of the shell beds indicates deposition under wave-generated currents. The sedimentary features and shell orientations indicate that the shell beds were deposited during storm events and not by the gradual accumulation of shelly material. Cluster and principal component analysis of relative abundance data of the taxa in the shell beds, interbedded nodular wackestones and mudstones, and laminated mudstones and shales, indicates one biofacies comprised of three main assemblages: a strophomenid (Sowerbyelladominated) assemblage, a transitional mixed strophomenid-atrypid assemblage and an atrypid (Zygospira-dominatQd) assemblage. The occurrence of the strophomenid, the strophomenid-atrypid and atrypid assemblages were controlled by storm-driven allogenic taphonomic feedback.

Aspergillus flavus infections in Galleria mellonella : a pathogen-host model system for the study of emerging diseases

To study emerging diseases, I employed a model pathogen-host system involving infections of insect larvae with the opportunistic fungus Aspergillus flavus, providing insight into three mechanisms ofpathogen evolution namely de novo mutation, genome decay, and virulence factoracquisition In Chapter 2 as a foundational experiment, A. flavus was serially propagated through insects to study the evolution of an opportunistic pathogen during repeated exposure to a single host. While A. flavus displayed de novo phenotypic alterations, namely decreased saprobic capacity, analysis of genotypic variation in Chapter 3 signified a host-imposed bottleneck on the pathogen population, emphasizing the host's role in shaping pathogen population structure. Described in Chapter 4, the serial passage scheme enabled the isolation of an A. flavus cysteine/methionine auxotroph with characteristics reminiscent of an obligate insect pathogen, suggesting that lost biosynthetic capacity may restrict host range based on nutrient availability and provide selection pressure for further evolution. As outlined in Chapter 6, cysteine/methionine auxotrophy had the pleiotrophic effect of increasing virulence factor production, affording the slow-growing auxotroph with a modified pathogenic strategy such that virulence was not reduced. Moreover in Chapter 7, transformation with a virulence factor from a facultative insect pathogen failed to increase virulence, demonstrating the necessity of an appropriate genetic background for virulence factor acquisition to instigate pathogen evolution.