918 resultados para Disease Models
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Economic losses resulting from disease development can be reduced by accurate and early detection of plant pathogens. Early detection can provide the grower with useful information on optimal crop rotation patterns, varietal selections, appropriate control measures, harvest date and post harvest handling. Classical methods for the isolation of pathogens are commonly used only after disease symptoms. This frequently results in a delay in application of control measures at potentially important periods in crop production. This paper describes the application of both antibody and DNA based systems to monitor infection risk of air and soil borne fungal pathogens and the use of this information with mathematical models describing risk of disease associated with environmental parameters.
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Thesis (Master's)--University of Washington, 2016-09
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Introduction The objectives of this thesis are to: (1) examine how ambulatory blood pressure monitoring (ABPM) refines office blood pressure (BP) measurement; (2) determine if absolute ambulatory BP or dipping status is better associated with target organ damage (TOD); (3) explore the association of isolated nocturnal hypertension (INH) with TOD; and (4) investigate the association of night-time BP with ultrasound markers of cardiovascular damage. Methods Data from the Mitchelstown Cohort Study was analysed to deliver objectives 1 and 2. Objective 3 was addressed by a systematic review and analysis of data from the Mitchelstown Study. A sample of participants from the Mitchelstown Study underwent an echocardiogram for speckle tracking analysis and carotid ultrasound to achieve objective 4. Results ABPM reclassifies hypertension status in approximately a quarter of individuals, with white coat and masked hypertension prevalence rates of 11% and 13% respectively. Night-time systolic BP is better associated with TOD than daytime systolic BP and dipping level. In multi-variable models the odds ratio (OR) for LVH was 1.4 (95% CI 1.1 -1.8) and for albumin:creatinine ratio ≥ 1.1 mg/mmol was 1.5 (95% CI 1.2 – 1.8) for each 10 mmHg rise in night-time systolic BP. The evidence for the association of INH with TOD is inconclusive. Night-time systolic BP is significantly associated with global longitudinal strain (GLS) (beta coefficient 0.85 for every 10 mmHg rise, 95% CI 0.3 – 1.4) and carotid plaques (OR 1.9 for every 10 mmHg rise, 95% CI 1.1 – 3.2) in univariable analysis. The findings persist for GLS in sex and age adjusted models but not in multivariable models. Discussion Hypertension cannot be effectively managed without using ABPM. Night-time systolic BP is better associated with TOD than daytime systolic BP and dipping level, and therefore, may be a better therapeutic target in future studies.
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Duchenne muscular dystrophy (DMD) is a neuromuscular disease caused by mutations in the dystrophin gene. DMD is clinically characterized by severe, progressive and irreversible loss of muscle function, in which most patients lose the ability to walk by their early teens and die by their early 20’s. Impaired intracellular calcium (Ca2+) regulation and activation of cell degradation pathways have been proposed as key contributors to DMD disease progression. This dissertation research consists of three studies investigating the role of intracellular Ca2+ in skeletal muscle dysfunction in different mouse models of DMD. Study one evaluated the role of Ca2+-activated enzymes (proteases) that activate protein degradation in excitation-contraction (E-C) coupling failure following repeated contractions in mdx and dystrophin-utrophin null (mdx/utr-/-) mice. Single muscle fibers from mdx/utr-/- mice had greater E-C coupling failure following repeated contractions compared to fibers from mdx mice. Moreover, protease inhibition during these contractions was sufficient to attenuate E-C coupling failure in muscle fibers from both mdx and mdx/utr-/- mice. Study two evaluated the effects of overexpressing the Ca2+ buffering protein sarcoplasmic/endoplasmic reticulum Ca2+-ATPase 1 (SERCA1) in skeletal muscles from mdx and mdx/utr-/- mice. Overall, SERCA1 overexpression decreased muscle damage and protected the muscle from contraction-induced injury in mdx and mdx/utr-/- mice. In study three, the cellular mechanisms underlying the beneficial effects of SERCA1 overexpression in mdx and mdx/utr-/- mice were investigated. SERCA1 overexpression attenuated calpain activation in mdx muscle only, while partially attenuating the degradation of the calpain target desmin in mdx/utr-/- mice. Additionally, SERCA1 overexpression decreased the SERCA-inhibitory protein sarcolipin in mdx muscle but did not alter levels of Ca2+ regulatory proteins (parvalbumin and calsequestrin) in either dystrophic model. Lastly, SERCA1 overexpression blunted the increase in endoplasmic reticulum stress markers Grp78/BiP in mdx mice and C/EBP homologous protein (CHOP) in mdx and mdx/utr-/- mice. Overall, findings from the studies presented in this dissertation provide new insight into the role of Ca2+ in muscle dysfunction and damage in different dystrophic mouse models. Further, these findings support the overall strategy for improving intracellular Ca2+ control for the development of novel therapies for DMD.
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Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.
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Although tyrosine kinase inhibitors (TKIs) such as imatinib have transformed chronic myelogenous leukemia (CML) into a chronic condition, these therapies are not curative in the majority of cases. Most patients must continue TKI therapy indefinitely, a requirement that is both expensive and that compromises a patient's quality of life. While TKIs are known to reduce leukemic cells' proliferative capacity and to induce apoptosis, their effects on leukemic stem cells, the immune system, and the microenvironment are not fully understood. A more complete understanding of their global therapeutic effects would help us to identify any limitations of TKI monotherapy and to address these issues through novel combination therapies. Mathematical models are a complementary tool to experimental and clinical data that can provide valuable insights into the underlying mechanisms of TKI therapy. Previous modeling efforts have focused on CML patients who show biphasic and triphasic exponential declines in BCR-ABL ratio during therapy. However, our patient data indicates that many patients treated with TKIs show fluctuations in BCR-ABL ratio yet are able to achieve durable remissions. To investigate these fluctuations, we construct a mathematical model that integrates CML with a patient's autologous immune response to the disease. In our model, we define an immune window, which is an intermediate range of leukemic concentrations that lead to an effective immune response against CML. While small leukemic concentrations provide insufficient stimulus, large leukemic concentrations actively suppress a patient's immune system, thus limiting it's ability to respond. Our patient data and modeling results suggest that at diagnosis, a patient's high leukemic concentration is able to suppress their immune system. TKI therapy drives the leukemic population into the immune window, allowing the patient's immune cells to expand and eventually mount an efficient response against the residual CML. This response drives the leukemic population below the immune window, causing the immune population to contract and allowing the leukemia to partially recover. The leukemia eventually reenters the immune window, thus stimulating a sequence of weaker immune responses as the two populations approach equilibrium. We hypothesize that a patient's autologous immune response to CML may explain the fluctuations in BCR-ABL ratio that are regularly seen during TKI therapy. These fluctuations may serve as a signature of a patient's individual immune response to CML. By applying our modeling framework to patient data, we are able to construct an immune profile that can then be used to propose patient-specific combination therapies aimed at further reducing a patient's leukemic burden. Our characterization of a patient's anti-leukemia immune response may be especially valuable in the study of drug resistance, treatment cessation, and combination therapy.
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Abnormalities in brains of Alzheimer's disease (AD) patients are thought to start long before the first clinical symptoms emerge. The identification of affected individuals at this 'preclinical AD' stage relies on biomarkers such as decreased levels of the amyloid-β peptide (Aβ) in the cerebrospinal fluid (CSF) and positive amyloid positron emission tomography scans. However, there is little information on the longitudinal dynamics of CSF biomarkers, especially in the earliest disease stages when therapeutic interventions are likely most effective. To this end, we have studied CSF Aβ changes in three Aβ precursor protein transgenic mouse models, focusing our analysis on the initial Aβ deposition, which differs significantly among the models studied. Remarkably, while we confirmed the CSF Aβ decrease during the extended course of brain Aβ deposition, a 20-30% increase in CSF Aβ40 and Aβ42 was found around the time of the first Aβ plaque appearance in all models. The biphasic nature of this observed biomarker changes stresses the need for longitudinal biomarker studies in the clinical setting and the search for new 'preclinical AD' biomarkers at even earlier disease stages, by using both mice and human samples. Ultimately, our findings may open new perspectives in identifying subjects at risk for AD significantly earlier, and in improving the stratification of patients for preventive treatment strategies.
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The investigation of pathogen persistence in vector-borne diseases is important in different ecological and epidemiological contexts. In this thesis, I have developed deterministic and stochastic models to help investigating the pathogen persistence in host-vector systems by using efficient modelling paradigms. A general introduction with aims and objectives of the studies conducted in the thesis are provided in Chapter 1. The mathematical treatment of models used in the thesis is provided in Chapter 2 where the models are found locally asymptotically stable. The models used in the rest of the thesis are based on either the same or similar mathematical structure studied in this chapter. After that, there are three different experiments that are conducted in this thesis to study the pathogen persistence. In Chapter 3, I characterize pathogen persistence in terms of the Critical Community Size (CCS) and find its relationship with the model parameters. In this study, the stochastic versions of two epidemiologically different host-vector models are used for estimating CCS. I note that the model parameters and their algebraic combination, in addition to the seroprevalence level of the host population, can be used to quantify CCS. The study undertaken in Chapter 4 is used to estimate pathogen persistence using both deterministic and stochastic versions of a model with seasonal birth rate of the vectors. Through stochastic simulations we investigate the pattern of epidemics after the introduction of an infectious individual at different times of the year. The results show that the disease dynamics are altered by the seasonal variation. The higher levels of pre-existing seroprevalence reduces the probability of invasion of dengue. In Chapter 5, I considered two alternate ways to represent the dynamics of a host-vector model. Both of the approximate models are investigated for the parameter regions where the approximation fails to hold. Moreover, three metrics are used to compare them with the Full model. In addition to the computational benefits, these approximations are used to investigate to what degree the inclusion of the vector population in the dynamics of the system is important. Finally, in Chapter 6, I present the summary of studies undertaken and possible extensions for the future work.
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Cranial cruciate ligament (CCL) deficiency is the leading cause of lameness affecting the stifle joints of large breed dogs, especially Labrador Retrievers. Although CCL disease has been studied extensively, its exact pathogenesis and the primary cause leading to CCL rupture remain controversial. However, weakening secondary to repetitive microtrauma is currently believed to cause the majority of CCL instabilities diagnosed in dogs. Techniques of gait analysis have become the most productive tools to investigate normal and pathological gait in human and veterinary subjects. The inverse dynamics analysis approach models the limb as a series of connected linkages and integrates morphometric data to yield information about the net joint moment, patterns of muscle power and joint reaction forces. The results of these studies have greatly advanced our understanding of the pathogenesis of joint diseases in humans. A muscular imbalance between the hamstring and quadriceps muscles has been suggested as a cause for anterior cruciate ligament rupture in female athletes. Based on these findings, neuromuscular training programs leading to a relative risk reduction of up to 80% has been designed. In spite of the cost and morbidity associated with CCL disease and its management, very few studies have focused on the inverse dynamics gait analysis of this condition in dogs. The general goals of this research were (1) to further define gait mechanism in Labrador Retrievers with and without CCL-deficiency, (2) to identify individual dogs that are susceptible to CCL disease, and (3) to characterize their gait. The mass, location of the center of mass (COM), and mass moment of inertia of hind limb segments were calculated using a noninvasive method based on computerized tomography of normal and CCL-deficient Labrador Retrievers. Regression models were developed to determine predictive equations to estimate body segment parameters on the basis of simple morphometric measurements, providing a basis for nonterminal studies of inverse dynamics of the hind limbs in Labrador Retrievers. Kinematic, ground reaction forces (GRF) and morphometric data were combined in an inverse dynamics approach to compute hock, stifle and hip net moments, powers and joint reaction forces (JRF) while trotting in normal, CCL-deficient or sound contralateral limbs. Reductions in joint moment, power, and loads observed in CCL-deficient limbs were interpreted as modifications adopted to reduce or avoid painful mobilization of the injured stifle joint. Lameness resulting from CCL disease affected predominantly reaction forces during the braking phase and the extension during push-off. Kinetics also identified a greater joint moment and power of the contralateral limbs compared with normal, particularly of the stifle extensor muscles group, which may correlate with the lameness observed, but also with the predisposition of contralateral limbs to CCL deficiency in dogs. For the first time, surface EMG patterns of major hind limb muscles during trotting gait of healthy Labrador Retrievers were characterized and compared with kinetic and kinematic data of the stifle joint. The use of surface EMG highlighted the co-contraction patterns of the muscles around the stifle joint, which were documented during transition periods between flexion and extension of the joint, but also during the flexion observed in the weight bearing phase. Identification of possible differences in EMG activation characteristics between healthy patients and dogs with or predisposed to orthopedic and neurological disease may help understanding the neuromuscular abnormality and gait mechanics of such disorders in the future. Conformation parameters, obtained from femoral and tibial radiographs, hind limb CT images, and dual-energy X-ray absorptiometry, of hind limbs predisposed to CCL deficiency were compared with the conformation parameters from hind limbs at low risk. A combination of tibial plateau angle and femoral anteversion angle measured on radiographs was determined optimal for discriminating predisposed and non-predisposed limbs for CCL disease in Labrador Retrievers using a receiver operating characteristic curve analysis method. In the future, the tibial plateau angle (TPA) and femoral anteversion angle (FAA) may be used to screen dogs suspected of being susceptible to CCL disease. Last, kinematics and kinetics across the hock, stifle and hip joints in Labrador Retrievers presumed to be at low risk based on their radiographic TPA and FAA were compared to gait data from dogs presumed to be predisposed to CCL disease for overground and treadmill trotting gait. For overground trials, extensor moment at the hock and energy generated around the hock and stifle joints were increased in predisposed limbs compared to non predisposed limbs. For treadmill trials, dogs qualified as predisposed to CCL disease held their stifle at a greater degree of flexion, extended their hock less, and generated more energy around the stifle joints while trotting on a treadmill compared with dogs at low risk. This characterization of the gait mechanics of Labrador Retrievers at low risk or predisposed to CCL disease may help developing and monitoring preventive exercise programs to decrease gastrocnemius dominance and strengthened the hamstring muscle group.
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Viruses play a key role in the complex aetiology of bovine respiratory disease (BRD). Bovine viral diarrhoea virus 1 (BVDV-1) is widespread in Australia and has been shown to contribute to BRD occurrence. As part of a prospective longitudinal study on BRD, effects of exposure to BVDV-1 on risk of BRD in Australian feedlot cattle were investigated. A total of 35,160 animals were enrolled at induction (when animals were identified and characteristics recorded), held in feedlot pens with other cattle (cohorts) and monitored for occurrence of BRD over the first 50 days following induction. Biological samples collected from all animals were tested to determine which animals were persistently infected (PI) with BVDV-1. Data obtained from the Australian National Livestock Identification System database were used to determine which groups of animals that were together at the farm of origin and at 28 days prior to induction (and were enrolled in the study) contained a PI animal and hence to identify animals that had probably been exposed to a PI animal prior to induction. Multi-level Bayesian logistic regression models were fitted to estimate the effects of exposure to BVDV-1 on the risk of occurrence of BRD.Although only a total of 85 study animals (0.24%) were identified as being PI with BVDV-1, BVDV-1 was detected on quantitative polymerase chain reaction in 59% of cohorts. The PI animals were at moderately increased risk of BRD (OR 1.9; 95% credible interval 1.0-3.2). Exposure to BVDV-1 in the cohort was also associated with a moderately increased risk of BRD (OR 1.7; 95% credible interval 1.1-2.5) regardless of whether or not a PI animal was identified within the cohort. Additional analyses indicated that a single quantitative real-time PCR test is useful for distinguishing PI animals from transiently infected animals.The results of the study suggest that removal of PI animals and/or vaccination, both before feedlot entry, would reduce the impact of BVDV-1 on BRD risk in cattle in Australian feedlots. Economic assessment of these strategies under Australian conditions is required. © 2016 Elsevier B.V.
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Cellular models are important tools in various research areas related to colorectal biology and associated diseases. Herein, we review the most widely used cell lines and the different techniques to grow them, either as cell monolayer, polarized two-dimensional epithelia on membrane filters, or as three-dimensional spheres in scaffoldfree or matrix-supported culture conditions. Moreover, recent developments, such as gut-on-chip devices or the ex vivo growth of biopsy-derived organoids, are also discussed. We provide an overview on the potential applications but also on the limitations for each of these techniques, while evaluating their contribution to provide more reliable cellular models for research, diagnostic testing, or pharmacological validation related to colon physiology and pathophysiology.
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The under-reporting of cases of infectious diseases is a substantial impediment to the control and management of infectious diseases in both epidemic and endemic contexts. Information about infectious disease dynamics can be recovered from sequence data using time-varying coalescent approaches, and phylodynamic models have been developed in order to reconstruct demographic changes of the numbers of infected hosts through time. In this study I have demonstrated the general concordance between empirically observed epidemiological incidence data and viral demography inferred through analysis of foot-and-mouth disease virus VP1 coding sequences belonging to the CATHAY topotype over large temporal and spatial scales. However a more precise and robust relationship between the effective population size (
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Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.
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Background: The -819C/T polymorphism in interleukin 10 (IL-10) gene has been reported to be associated with inflammatory bowel disease (IBD) ,but the previous results are conflicting. Materials and Methods: The present study aimed at investigating the association between this polymorphism and risk of IBD using a meta-analysis.PubMed,Web of Science,EMBASE,google scholar and China National Knowledge Infrastructure (CNKI) databases were systematically searched to identify relevant publications from their inception to April 2016.Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated using fixed- or random-effects models. Results: A total of 7 case-control studies containing 1890 patients and 2929 controls were enrolled into this meta-analysis, and our results showed no association between IL-10 gene -819C/T polymorphism and IBD risk(TT vs. CC:OR=0.81,95%CI 0.64- 1.04;CT vs. CC:OR=0.92,95%CI 0.81-1.05; Dominant model: OR=0.90,95%CI 0.80-1.02; Recessive model: OR=0.84,95%CI 0.66-1.06). In a subgroup analysis by nationality, the -819C/T polymorphism was not associated with IBD in both Asians and Caucasians. In the subgroup analysis stratified by IBD type, significant association was found in Crohn’s disease(CD)(CT vs. CC:OR=0.68,95%CI 0.48-0.97). Conclusion: In summary, the present meta-analysis suggests that the IL-10 gene -819C/T polymorphism may be associated with CD risk.
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Friedreich ataxia (FRDA) is the most common form of autosomal-recessive ataxia. Common nonmotor features include cardiomyopathy and diabetes mellitus. At present, no effective treatments are available to prevent disease progression. Age of onset varies from infancy to adulthood. In the majority of patients, FRDA is caused by intronic GAA expansions in FXN, which encodes a highly-conserved small mitochondrial matrix protein, frataxin. A mouse model of FRDA has been difficult to generate because complete loss of frataxin causes early embryonic lethality. Although there are some controversies about the function of frataxin, recent biochemical and structural studies have confirmed that it is a component of the multiprotein complex that assembles iron-sulfur clusters in the mitochondrial matrix. The main consequences of frataxin deficiency are energy deficit, altered iron metabolism, and oxidative damage.