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1
Harris, Bertha J. "Veteran Administration Disease Model to an Interdisciplinary Healthcare Model." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6574.
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There is a growing need for healthcare teams within the Veterans Administration (VA) healthcare system to effectively collaborate and communicate to improve patient outcomes. The need to improve patient care in the Patient Aligned Care Team (PACT) has been well established. The scholarly literature does not provide evidence whether using the primary care PACT model on communication and teamwork by an interdisciplinary medical team ameliorates these communication breakdowns. Bronstein's design for interdisciplinary collaboration provided the overarching framework for this study. The purpose of this qualitative case study was to investigate the use of the PACT model on communication and teamwork by an interdisciplinary medical team as well as the perceived processes and results that the interdisciplinary collaborative approach has on production data. 18 participants consisted of licensed medical professionals and other licensed and non-licensed support personnel who were part of the PACT team. There were several challenges associated with the model, such as (a) a lack of clearly defined roles, (b) lack of communication and collaboration, and (c) division between the clerical and medical staff that created a hostile work environment. Other participants felt there were benefits associated with the PACT model, included (a) improved communication between team members, (b) increased collaboration among team members, and (c) enhanced care for patients using a comprehensive team approach. These findings may help leaders create policies, improve patient care, and create perceived processes to affect successful long-term programs for the future implementation of the PACT model.
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Tepper, Sherri. "A biopsychosocial model of Alzheimer's disease /." Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=59861.
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Research on the etiological characteristics of Alzheimer's disease has yielded inconsistent results. It is suggested that this may be due to the unidirectional focus on biomedical attributes, and the failure to consider psychosocial factors in combination with the biomedical characteristics. A biopsychosocial model of Alzheimer's disease, which integrates the biomedical dimension with psychosocial stressors and social support is proposed and tested in a sample of 172 geriatric patients using polychotomous logistic regression. Results find support for the implication of stress in the disease process, but fail to find a relationship between social support and Alzheimer's disease. It is concluded that the ultimate value of a biopsychosocial model of Alzheimer's disease rests in its identification of psychosocial factors, that could result in the prevention of the development of the disease.
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Lawson, Kenneth Daniel. "The Scottish cardiovascular disease policy model." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4695/.
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This thesis is concerned with economic evaluation in the primary prevention of cardiovascular disease. Policymakers are increasingly focussed on reducing the health and economic burden of CVD and to reduce health inequalities. However, the approach to primary prevention suffers from fundamental weaknesses that this research intends to help address. There is general lack of effectiveness and cost effectiveness evidence underpinning current primary prevention interventions. First, there is a policy impetus towards mass screening strategies to target individuals at high risk of developing CVD when more focussed approaches may be more cost effective. Second, clinicians prioritise individuals on the basis of 10-year risk scores, which are strongly driven by age, and not the potential benefits (or costs) from treatment. Third, targeted and population interventions are often still treated as competing approaches, whereas the key issue is how they might best combine. The key premise of this thesis is that the aims of primary prevention are the avoidance of premature morbidity, mortality and to close health inequalities - subject to a budget constraint. A CVD Policy Model was created using the same nine risk factors as used in the ASSIGN 10-year risk score, currently used in clinical practice in Scotland, to estimate life expectancy, quality adjusted life expectancy and lifetime hospital costs. This model can be employed to estimate the cost effectiveness of interventions and the impact on health inequalities. The model performed well in a comprehensive validation process in terms of face validity, internal validity, and external validity. Life expectancy predictions were re-calibrated to contemporary lifetables. This generic modelling approach (i.e. using a wide range of inputs and producing a wide range of outputs) is intended to avoid the need to build bespoke models for different interventions aimed at particular risk factors or to produce particular outputs. In application, the CVD Policy Model is intended to assist clinicians and policymakers to develop a more coherent approach to primary prevention, namely: to design more efficient screening strategies; prioritise individuals for intervention on the basis of potential benefit (rather than risk); and to assess the impact of both individually targeted and population interventions on a consistent basis. Using the model in these ways may enable primary prevention approaches to be more consistent with guidelines from health sector reimbursement agencies, which may result in a more efficient use of scarce resources.
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Leung, Wai Keung. "Effects of Treponema denticola on an oral epithelial cell model." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0009/NQ34575.pdf.
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Thompson, Brett Morinaga. "Development, Implementation, and Analysis of a Contact Model for an Infectious Disease." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc9824/.
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With a growing concern of an infectious diseases spreading in a population, epidemiology is becoming more important for the future of public health. In the past epidemiologist used existing data of an outbreak to help them determine how an infectious disease might spread in the future. Now with computational models, they able to analysis data produced by these models to help with prevention and intervention plans. This paper looks at the design, implementation, and analysis of a computational model based on the interactions of the population between individuals. The design of the working contact model looks closely at the SEIR model used as the foundation and the two timelines of a disease. The implementation of the contact model is reviewed while looking closely at data structures. The analysis of the experiments provide evidence this contact model can be used to help epidemiologist study the spread of an infectious disease based on the contact rate of individuals.
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Costa, Marc Michael John Da. "A zebrafish model of motor neurone disease." Thesis, University of Sheffield, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548470.
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Hoffman, Lori A. "Disease Gene Mapping Under The Coalescent Model." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1282058674.
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Huang, Shuang, and Shuang Huang. "Regularized Markov Model for Modeling Disease Transitioning." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/625633.
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In longitudinal studies of chronic diseases, the disease states of individuals are often collected at several pre-scheduled clinical visits, but the exact states and the times of transitioning from one state to another between observations are not observed. This is commonly referred to as "panel data". Statistical challenges arise in panel data in regard to identifying predictors governing the transitions between different disease states with only the partially observed disease history. Continuous-time Markov models (CTMMs) are commonly used to analyze panel data, and allow maximum likelihood estimations without making any assumptions about the unobserved states and transition times. By assuming that the underlying disease process is Markovian, CTMMs yield tractable likelihood. However, CTMMs generally allow covariate effect to differ for different transitions, resulting in a much higher number of coefficients to be estimated than the number of covariates, and model overfitting can easily happen in practice. In three papers, I develop a regularized CTMM using the elastic net penalty for panel data, and implement it in an R package. The proposed method is capable of simultaneous variable selection and estimation even when the dimension of the covariates is high.
In the first paper (Section 2), I use elastic net penalty to regularize the CTMM, and derive an efficient coordinate descent algorithm to solve the corresponding optimization problem. The algorithm takes advantage of the multinomial state distribution under the non-informative observation scheme assumption to simplify computation of key quantities. Simulation study shows that this method can effectively select true non-zero predictors while reducing model size.
In the second paper (Section 3), I extend the regularized CTMM developed in the previous paper to accommodate exact death times and censored states. Death is commonly included as an endpoint in longitudinal studies, and exact time of death can be easily obtained but the state path leading to death is usually unknown. I show that exact death times result in a very different form of likelihood, and the dependency of death time on the model requires significantly different numerical methods for computing the derivatives of the log likelihood, a key quantity for the coordinate descent algorithm. I propose to use numerical differentiation to compute the derivatives of the log likelihood. Computation of the derivatives of the log likelihood from a transition involving a censored state is also discussed. I carry out a simulation study to evaluate the performance of this extension, which shows consistently good variable selection properties and comparable prediction accuracy compared to the oracle models where only true non-zero coefficient are fitted. I then apply the regularized CTMM to the airflow limitation data to the TESAOD (The Tucson Epidemiological Study of Airway Obstructive Disease) study with exact death times and censored states, and obtain a prediction model with great size reduction from a total of 220 potential parameters.
Methods developed in the first two papers are implemented in an R package markovnet, and a detailed introduction to the key functionalities of the package is demonstrated with a simulated data set in the third paper (Section 4). Finally, some conclusion remarks are given and directions to future work are discussed (Section 5).
The outline for this dissertation is as follows. Section 1 presents an in-depth background regarding panel data, CTMMs, and penalized regression methods, as well as an brief description of the TESAOD study design. Section 2 describes the first paper entitled "Regularized continuous-time Markov model via elastic net'". Section 3 describes the second paper entitled "Regularized continuous-time Markov model with exact death times and censored states"'. Section 4 describes the third paper "Regularized continuous-time Markov model for panel data: the markovnet package for R"'. Section 5 gives an overall summary and a discussion of future work.
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Whitehead, Daisy. "Hallucinations in Parkinson's disease : a psychological model." Thesis, University of Liverpool, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415741.
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Gupta, Amrita. "Unsupervised learning of disease subtypes from continuous time Hidden Markov Models of disease progression." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54364.
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The detection of subtypes of complex diseases has important implications for diagnosis and treatment. Numerous prior studies have used data-driven approaches to identify clusters of similar patients, but it is not yet clear how to best specify what constitutes a clinically meaningful phenotype. This study explored disease subtyping on the basis of temporal development patterns. In particular, we attempted to differentiate infants with autism spectrum disorder into more fine-grained classes with distinctive patterns of early skill development. We modeled the progression of autism explicitly using a continuous-time hidden Markov model. Subsequently, we compared subjects on the basis of their trajectories through the model state space. Two approaches to subtyping were utilized, one based on time-series clustering with a custom distance function and one based on tensor factorization. A web application was also developed to facilitate the visual exploration of our results. Results suggested the presence of 3 developmental subgroups in the ASD outcome group. The two subtyping approaches are contrasted and possible future directions for research are discussed.
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Bernard, Branka. "Huntington's disease." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2009. http://dx.doi.org/10.18452/15900.
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Die Huntington''sche Krankheit (Huntington''s disease, HD) ist eine tödliche neurodegenerative Erkrankung mit einem extensiven Verlust von Neuronen im Striatum. Die Ursache für HD ist eine genetische Mutation, bei der eine CAG-Wiederholungssequenz verlängert wird. Im resultierenden Protein, das Huntingtin (htt) genannt wurde, diese Mutation führt zur Missfaltung und Aggregation von htt. Ich habe untersucht ob die Bildung von htt-Aggregaten die Transkription von Genen dass sie von HD-assoziierten Transkriptionsfaktoren kontrolliert werden, verändert. Zur Untersuchung der Transkription wurden die zu untersuchenden Gene auf cDNA-Mikroarrays aufgebracht und mit RNA, welche aus den Zellen nach der Induktion der Expression des mutierten htt gewonnen wurde, hybridisiert. Es wurden keine systematischen Veränderungen innerhalb der durch spezifische Transkriptionsfaktoren regulierten Gengruppen gefunden. Ich habe auch mehrere mathematische Modelle erstellt, welche die htt-Aggregation und den Zelltod beschreiben. Die Ergebnisse zeigten, dass eine transiente Dynamik im System und die nicht-monotone Reaktion auf Parameteränderungen zu den nicht-intuitiven Ergebnissen bei Behandlungsansätzen, welche die htt-Aggregation beeinflussen, führen könnten. Für den Fall, dass Aggregate die toxische Form von htt sind, zeigten die numerischen Simulationen dass das Einsetzen der Aggregation, welches durch ein Überschießen der Aggregatkonzentration gekennzeichnet ist, am ehesten zum Zelltod führt. Dieses Phänomen wurde "one-shot"-Modell genannt. Es gibt, auch bei HD-Patienten mit gleicher Länge der CAG-Wiederholungssequenz, eine große Varianz des Alters bei Krankheitsausbruch (age of onset, AO). Ich habe ein stochastisches Modell für den neuronalen Zelltod im Striatum entwickelt. Das Modell zeigte, dass ein signifikanter Anteil der nicht erklärbaren Varianz des AO der intrinsischen Dynamik der Neurodegeneration zugeschrieben werden kann.Huntington''s disease (HD) is a fatal neurodegenerative disorder characterized by a progressive neuronal loss in the striatum of HD patients. HD is caused by a CAG repeat expansion which translates into a polyglutamine stretch at the N-terminus of the huntingtin protein (htt). The polyQ stretch induces misfolding, cleavage and aggregation of htt. To test the hypothesis that the sequestration of transcription factors into the htt aggregates causes transcriptional changes observed in HD models, I compiled lists of genes controlled by the transcription factors associated with HD. These genes were spotted on cDNA microarrays that were later hybridized with RNA extracted from cells expressing a mutant htt fragment. In this study, no systematic changes related to a specific transcription factors were observed. Formation and the accumulation of htt aggregates causes neurotoxicity in different HD model systems. To investigate the consequences of therapeutic strategies targeting aggregation, I derived several mathematical models describing htt aggregation and cell death. The results showed that transient dynamics and the non-monotonic response of cell survival to a change of parameter might lead to the non-intuitive outcome of a treatment that targets htt aggregation. Also, the numerical simulations show that if aggregates are toxic, the onset of aggregation, marked by the overshoot in the concentration of aggregates, is the event most likely to kill the cell. This phenomenon was termed a one-shot model. The principal cause of the variability of the age at onset (AO) is the length of the CAG repeat. Still, there is a great variance in the AO even for the same CAG repeat length. To study the variability of the AO, I developed a stochastic model for clustered neuronal death in the HD striatum. The model showed that a significant part of the unexplained variance can be attributed to the intrinsic stochastic dynamics of neurodegeneration.
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Liu, Jie. "Novel Bayesian Methods for Disease Mapping: An Application to Chronic Obstructive Pulmonary Disease." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0501102-110350.
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Thesis (M.S.)--Worcester Polytechnic Institute.Keywords: latent class model; Poisson regression model; Metropolis-Hastings sampler; order restriction; disease mapping. Includes bibliographical references.
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Pokrzywa, Malgorzata. "A Drosophila Disease-Model for Transthyretin-associated Amyloidosis." Doctoral thesis, Umeå : Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1677.
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Bodhicharla, Rakesh Kumar. "Transgenic nematodes as a model for Parkinson's disease." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/12108/.
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Aggregation of the abundant neural protein α-synuclein contributes to cellular toxicity in Parkinson‘s disease. We have created transgenic nematodes carrying fusion constructs encoding human α-synuclein (S) tagged with YFP (V) and/or CFP (C) as a fluorescent marker. Using the unc-54 myosin promoter, a synuclein-YFP (unc-54::SV (NI)) fusion construct was abundantly expressed in the body wall muscles of Caenorhabditis elegans. Permanent integrated lines were successfully generated for unc-54::V (NI), unc-54::S+V (I), unc-54::SC+SV (I), unc-54::C+V (I), and unc-54::CV (I) using gamma irradiation. The outcrossed transgenic synuclein strains were radiation sensitive and have shorter life span and lower pharyngeal pumping compared to wild type N2 and unc-54::V (I) worms. Fluorescence Resonance Energy Transfer (FRET) was measured for all the transgenic strains. The unc-54::SC+SV (I) worms showed FRET signals intermediate between the negative (unc-54::C+V (I)) and positive (unc-54::CV (I)) control strains. Confocal images were taken to confirm the presence of FRET. FRET signals increase markedly during early adult life in unc-54::SC+SV (I) worms. RNA interference by feeding was performed in unc-54::SC+SV (I) worms to knock out the Hip-1 co-chaperone function, thereby increasing the FRET signal. unc-54::SC+SV (I) fusion worms were also exposed to pesticides such as chlorpyrifos and rotenone, and we observed an increase in the size and intensity of fluorescent aggregates thereby increasing the FRET signal. Finally we have quantified reactive oxygen species (ROS) for unc-54::SC+SV (I) fusion worms and NL5901 strains by using the H2DCF-DA assay, showing that ROS levels were increased by pesticide exposure.
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Lee, Wyan-Ching Mimi. "Characterization of a Drosophila model of Huntington's disease." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/34571.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references.
Huntington's disease (HD) is an autosomal dominant neurological disorder caused by a polyglutamine (polyQ) repeat expansion in the huntingtin (Htt) protein. The disease is characterized by neurodegeneration and formation of neuronal intracellular inclusions primarily in the striatum and cortex, leading to personality changes, motor impairment, and dementia. To date, the molecular mechanisms that underlie the neurodegenerative process remain to be defined. Development of transgenic Drosophila HD models may facilitate dissection of molecular and cellular pathways that lead to disease pathology and suggest potential strategies for treatment. To explore mutant Htt-mediated mechanisms of neuronal dysfunction, we generated transgenic Drosophila that express the first 548 amino acids of the human Htt gene with either a pathogenic polyglutamine tract of 128 repeats (Htt-Q128) or a nonpathogenic tract of 0 repeats (Htt-QO). Characterization of these transgenic lines indicates formation of cytoplasmic and neuritic Htt aggregates in our Drosophila HD model that sequester other non-nuclear polyQ-containing proteins and block axonal transport.
(cont.) To further explore axonal transport defects in Huntington's disease, we generated Drosophila transgenic strains expressing 588 aa or exon 1 N-terminal fragments of human huntingtin encoding pathogenic (HttQ138) or nonpathogenic (HttQ15) proteins tagged with mRFP and/or eGFP. These transgenic lines enable in vivo imaging of Htt aggregation and trafficking in live Drosophila, providing a unique resource for tracking Htt in real time. Our findings indicate that expression of mutant Htt may impair axonal transport through both aggregate-dependent and -independent means. Finally, to assay the therapeutic effect of expression of an intracellular antibody (intrabody) against Htt, we generated double transgenic lines coexpressing pathogenic Htt (mRFP-HttQ138) with the V12.3 intrabody. Intrabody expression caused suppression of aggregation in both neuronal and non-neuronal cell types, but failed to rescue mutant Htt-mediated cellular dysfunction. In summary, our Drosophila HD model provides an ideal in vivo system for examination of mutant Htt-mediated cellular defects, particularly impairment of axonal transport, and may facilitate rapid development and validation of potential treatments for Huntington's disease.
b y Wyan-Ching Mimi Lee.
Ph.D.
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Moore, Nathan T. "Artificial Societies: A Computational Model of Disease Transmission." W&M ScholarWorks, 1999. https://scholarworks.wm.edu/etd/1539626823.
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Cartelli, D. "Microtubule dysfunction in experimental model of Parkinson's disease." Doctoral thesis, Università degli Studi di Milano, 2010. http://hdl.handle.net/2434/152043.
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Parkinson’s disease (PD) is the most common motor neurodegenerative disorder, affecting 1% of people at age of 65 and, and its cardinal symptoms are resting tremors, rigidity and bradykinesia. Now, it is well established that the clinical features of PD are due to the degeneration dopaminergic neurons residing in the substantia nigra and projecting to the striatum. There is no a conclusive demonstration that PD is an environmental or a genetic disease, but there is agreement about the fact that PD could be a multifactorial disorder and that the greater risk factor is the age. So, in attempt to elucidate molecular mechanisms of dopaminergic cell death, useful are both toxin-based and gene-based models. At the present time, there are several hypothesis about the molecular pathways leading to PD. Just to have a brief overview, toxin-induced model opened the way to the concept that mitochondrial dysfunction are the initial insult, because all toxins induce the formation of ROS, reduce ATP production and for some of them is clearly demonstrated an inhibition of the complex I of the respiratory chain. Two are the main hypothesis coming from genetic models of PD: ubiquitin-proteasome system (UPS) dysfunction, that acting in concert with the reduction of autophagy, seems to overload the cell with damaged proteins; oligomerization and aggregation of misfolded and/or unfolded proteins, that could act subtracting useful monomers, or through the formation of toxic oligomers. Flanking these large accepted mechanisms of degeneration in PD, is emerging a new possible cause of neuron dysfunction: microtubule (MT) dysfunction. MTs are a common target of PD-inducing neurotoxins, as rotenone and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), and mutated proteins in PD, as synuclein and parkin. MT dysfunction could trigger cell death by axonal transport impairment, a common mechanism described in many neurodegenerative diseases.
The present study was designed to investigate the putative role of MT dysfunction in diverse models of PD, ranging from neurotoxic model represented by MPTP, to genetic model, i.e. synuclein and parkin. The implication of MT alterations have been investigated at different levels, from molecular level using purified protein system, to complex system as an animal model is, passing through cell cultures.
Particularly, we analyzed MT dysfunctions in PC12 cells treated with 1-methyl-4-phenyl-pyridinium (MPP+), the toxic metabolite of MPTP, and their relationship with known alterations induced by the neurotoxin as complex I block and impairment of axonal transport. In NGF-differentiated PC12 cells, we have analyzed post-translational modifications of tubulin known to be associated with differently dynamic MTs and show that MPP+ causes a selective loss of dynamic MTs and a concomitant enrichment of stable MTs. Through a direct live cell imaging approach we show a significant reduction of MT dynamics following exposure to MPP+ and a reorientation of MTs. Furthermore, these alterations precede the impairment of mitochondria transport along neurites. We have also analyzed activation of caspase-3 and mitochondrial injury, well known alterations induced by MPP+; in our experimental conditions, we found that they are noticeable only when MT dysfunction is already established. Furthermore, analysis of striatal lysates and sections revealed that alteration of MT stability is the first noticeable alterations in MPTP-treated mice, preceding mitochondrial accumulation and tyrosine hydroxylase (TH) depletion, a well accepted marker of dopaminergic degeneration progression. These data provide the first evidence that axonal transport impairment and mitochondrial damage are tightly associated with, and might be a consequence of MT dysfunction in MPTP-induced neurodegeneration.
Further, we investigated the effect of wild type and mutated synucleins on the polymerization kinetics of purified tubulin, and on MT structure. Wild type synuclein seems to stabilize MT structure promoting tubulin polymerization, whereas the pathologic mutants of synuclein elicit the opposite effects. In fact, they tend to broke the MT lattice and inhibit tubulin polymerization. The effect on tubulin polymerization kinetics that we observed, can suggest a physiological role of synuclein in regulating MT dynamic behavior and could be relevant from a pathogenic point of view. The MT destabilizing effects of mutant synucleins could interfere with the correct assembly of neuronal architecture, but also can impair axonal transport by breaking the railways along organelles move, leading to dopaminergic degeneration.
Finally, we investigated MT stability in mice lacking parkin. Using western blotting and immunofluorescence analysis, we show variations of tubulin post-translation modification in parkin null mice, both in striatum and substantia nigra. Analysis of mitochondria distribution and TH expression revealed that axonal transport seems to be blocked. Another one time, MT dysfunction is suggested as pivotal alteration in the chain of event leading to dopaminergic neuron death.
Putting all the pieces together, the data reported here show MTs as a common target of MPTP, synuclein and parkin. All these data make MT dysfunction an acceptable culprit of neurodegenerative process. Furthermore, the relationship between MPTP-induced MT dysfunction and the known alterations of mitochondria and axonal transport, and the fact that changes in MT stability are noticeable before any other signs of neurodegeneration in mice lacking parkin, strongly suggest a central and pivotal role of MT system in triggering neuronal death in PD.
Under this light, MTs could be a good “druggable” candidate for future prevention and PD therapies, that not only ameliorate the symptoms but that also restore the damaged tissue, improving the lifespan and the quality of life of PD patients
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Barker, Colin. "Genomic evaluation of models of human disease : the Fechm1pas model of erythropoietic protoporphyria." Thesis, University of Leicester, 2006. http://hdl.handle.net/2381/30778.
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Erythropoeitic protoporphyria (EPP) is a member of the prophyria disease class and is caused by abnormal function of the enzyme ferrochelatase (Fech). In humans it has variable penetrance, but primarily leads to toxicity in the skin and liver to varying degrees. Here I have investigated the nature of EPP progression using the Fechm1PAS mouse model. This mouse contains a point mutation in the fech gene which results in reduced Fech activity to < 7% of wild type, with resultant loss of haem, anaemia and hepatic cholestasis. The phenotypic progression of Fechm1PAS/m1PAS mice was established using pathology and clinical biochemistry from 18 days gestation to 32 weeks of age. Pathological changes were found from 4 weeks with biochemical and differential gene expression (DGE) analysis showing intraheptic cholestasis from birth. Genomic data from cDNA microarrays was derived and analysed with the DGE by phenotypic anchoring. DGE was observed in all processes responsible for cell protection and epigenetic regulation. DGE analysis have led me to hypothesise that the porphyria leads to a chronic reactive oxygen species (ROS) attack, causing DNA damage, eventually leading to hepatocarinoma. This was indicated by changes in the GSH, cytochrome P450, circadian rhythm and methylation pathways. DGE in these processes included downregulation of DNA methyltransferases (Dnmt1, Dnmt6a and Dnmt6b), and upregulation of cytochrome oxidase (Cox and Por) and GSH metabolism transcription factors (Gclc and Gclm). The findings made here contribute further to the understanding of EPP progression and the relationship between phenotype and DGE in EPP.
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Baker, Jannah F. "Bayesian spatiotemporal modelling of chronic disease outcomes." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/104455/1/Jannah_Baker_Thesis.pdf.
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This thesis contributes to Bayesian spatial and spatiotemporal methodology by investigating techniques for spatial imputation and joint disease modelling, and identifies high-risk individual profiles and geographic areas for type II diabetes mellitus (DMII) outcomes. DMII and related chronic conditions including hypertension, coronary arterial disease, congestive heart failure and chronic obstructive pulmonary disease are examples of ambulatory care sensitive conditions for which hospitalisation for complications is potentially avoidable with quality primary care. Bayesian spatial and spatiotemporal studies are useful for identifying small areas that would benefit from additional services to detect and manage these conditions early, thus avoiding costly sequelae.
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Kim, Sohee. "Computational modeling in Alzheimer's disease." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1267541374.
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Erdem, Munire Tugba. "Modeling Diseases With Multiple Disease Characteristics: Comparison Of Models And Estimation Methods." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613531/index.pdf.
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Epidemiological data with disease characteristic information can be modelled in several ways. One way is taking each disease characteristic as a response and constructing binary or polytomous logistic regression model. Second way is using a new response which consists of disease subtypes created by cross-classification of disease characteristic levels, and then constructing polytomous logistic regression model. The former may be disadvantageous since any possible covariation between disease characteristics is neglected, whereas the latter can capture that covariation behaviour. However, cross-classifying the characteristic levels increases the number of categories of response, so that dimensionality problem in parameter space may occur in classical polytomous logistic regression model. A two staged polytomous logistic regression model overcomes that dimensionality problem. In this thesis, study is progressen in two main directions: simulation study and data analysis parts. In simulation study, models that capture the covariation behaviour are compared in terms of the response model parameter estimators. That is, performances of the maximum likelihood estimation (MLE) approach to classical polytomous logistic regression, Bayesian estimation approach to classical polytomous logistic regression and pseudo-conditional likelihood (PCL) estimation approach to two stage polytomous logistic regression are compared in terms of bias and variation of estimators. Results of the simulation study revealed that for small sized sample and small number of disease subtypes, PCL outperforms in terms of bias and variance. For medium scaled size of total disease subtypes situation when sample size is small, PCL performs better than MLE, however when the sample size gets larger MLE has better performance in terms of standard errors of estimates. In addition, sampling variance of PCL estimators of two stage model converges to asymptotic variance faster than the ML estimators of classical polytomous logistic regression model. In data analysis, etiologic heterogeneity in breast cancer subtypes of Turkish female cancer patients is investigated, and the superiority of the two stage polytomous logistic regression model over the classical polytomous logistic model with disease subtypes is represented in terms of the interpretation of parameters and convenience in hypothesis testing.
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Ubina, Teresa Marie. "AN ISOGENIC STEM CELL MODEL OF ALZHEIMER'S DISEASE: DIRECT EXPRESSION OF AMYLOID-BETA." CSUSB ScholarWorks, 2017. https://scholarworks.lib.csusb.edu/etd/523.
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Alzheimer’s disease (AD), identified over 100 years ago and intensively studied since the 1970s, has no effective treatments or mechanistic understanding of the underlying neurodegenerative process. Most investigators believe accumulation or aggregation of amyloid beta (Ab) proteins plays a causative role. Aβ peptides (~39-43 residues) are generated by proteolysis of the transmembrane protein APP. One reason we know so little about AD is an incomplete understanding of the cellular mechanisms responsible for Ab proteotoxicity. Human ES and iPSC models of AD are recent additions to many other models used to investigate these mechanisms. AD, however is a chronic progressive condition of old age and cultured neurons may not live long enough to model what goes wrong in neurons from AD patients. In my research, I used hESCs which directly express Ab peptides thus avoiding the time it takes to process APP. One App allele in H9 hESCs was previously edited using TALEN. A homologous recombination cassette coding directly for a secretory form of either Ab1-42 or Ab1-40 and containing a stop codon, was inserted into the first exon of App upstream of the normal translational start site. I used multiple independently isolated clones of edited cells with 3 genotypes: App/App (unedited), App/Aβ1-40 and App/Aβ1-42. Expression of Ab from edited alleles was confirmed by qRT-PCR using primers specific for the edit. I first sought to establish if editing changed any aspects of neuronal differentiation in culture. All 3 genotypes have similar embryoid body (EB) development, and similar numbers and sizes of neuronal clusters (NC) up to 34 days after EB dissociation and neural differentiation. Immunostaining of neuronal markers, NeuN and DCX (doublecortin), likewise revealed no difference among edited and unedited cells, suggesting that the edits do not affect the ability of my stem cells to differentiate into neurons. I next measured accumulation of aggregated Ab using an aggregate specific antibody, 7A1a. Data at 34-days post EB dissociation indicates NCs in the Aβ1-42 edited cells accumulate significantly more aggregates relative to either unedited or Ab1-40 edited lines, a result consistent with the increased ability for Ab1-42 to form aggregates. Aβ aggregates also appear to be concentrated around fragmented nuclei within neuronal clusters suggesting that intracellular accumulation may play a key role in proteotoxicity. Additionally, I observed a significant decrease in the number of synapsin1 puncta, a marker of synapses, another feature of AD. I documented a nearly 3-fold greater neuronal cell death in both the Aβ1-40 and Aβ1-42 neurons at 70 days after differentiation. RNA sequencing data also shows independently isolated clones group together and show differential expression of genes related to memory and neuronal cell death. The early presence of Aβaggregation and subsequent cell death is in line with the chronic and progressive nature of AD and this is the first known model to exhibit a neurodegenerative phenotype. These isogenic cell lines thus appear to be useful to screen for therapeutics that may prevent or slow Ab1-42 dependent neurodegeneration and a tool to investigate Ab-dependent mechanisms with relevance to AD.
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Khechara, Martin Peter. "The nematode Caenorhabditis elegans as an alternative model for bacterial infection." Thesis, n.p, 2004. http://ethos.bl.uk/.
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Xing, Li. "Model and inference issues related to exposure-disease relationships." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50042.
Full textAbstract:
The goal of my thesis is to make contributions on some statistical issues related to epidemiological investigations of exposure-disease relationships.
Firstly, when the exposure data contain missing values and measurement errors, we build a Bayesian hierarchical model for relating disease to a potentially harmful exposure while accommodating these flaws. The traditional imputation method, called the group-based exposure assessment method, uses the group exposure mean to impute the individual exposure in that group, where the group indicator indicates that the exposure levels tend to vary more across groups and less within groups. We compare our method with the traditional method through simulation studies, a real data application, and theoretical calculation. We focus on cohort studies where a logistic disease model is appropriate and where group exposure means can be treated as fixed effects. The results show a variety of advantages of the fully Bayesian approach, and provide recommendations on situations where the traditional method may not be suitable to use.
Secondly, we investigate a number of issues surrounding inference and the shape of the exposure-disease relationship. Presuming that the relationship can be expressed in terms of regression coefficients and a shape parameter, we investigate how well the shape can be inferred in settings which might typify epidemiologic investigations and risk assessment. We also consider a suitable definition of the average effect of exposure, and investigate how precisely this can be inferred. We also examine the extent to which exposure measurement error distorts inference about the shape of the exposure-disease relationship. All these investigations require a family of exposure-disease relationships indexed by a shape parameter. For this purpose, we employ a family based on the Box-Cox transformation.
Thirdly, matching is commonly used to reduce confounding due to lack of randomization in the experimental design. However, ignoring measurement errors in matching variables will introduce systematically biased matching results. Therefore, we recommend to fit a trajectory model to the observed covariate and then use the estimated true values from the model to do the matching. In this way, we can improve the quality of matching in most cases.Science, Faculty of
Statistics, Department of
Graduate
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Horemuz, Michal. "Morphable Brain Model for Monitoring Disease Related Brain Changes." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-164967.
Full textAbstract:
Alzheimer's Disease is a devastating neurodegenerative disease that costs billions of dollars each year worldwide. Early diagnosis of the disease can greatly improve patients well-being. There are computer-aided methods that can detect the disease using high quality brain scans. However, these kinds of scans are very rare in the clinic so the methods are not applicable. This paper explores methods for detecting Alzheimer's Disease based on deformation fields of brain scans. This has the advantage of being robust to intensity error, and thus applicable on lower quality scans. The methods were tested using low quality MRI scans, with a slice thickness of 5.5mm. Using a morphable model, which captures the general shape of a brain, the result of classifying diseased and healthy brains had 94/97/92 accuracy/sensitivity/specificity, which is comparable to other methods which use high quality images. This result suggests it may be possible to use methods based on deformation fields in research using clinical data, and possibly for clinical use as well.Alzheimers sjukdom är en förödande neurodegenerativ sjukdom som kostar hela världen miljarder dollar årligen. Tidig diagnos av sjukdomen kan forbattra patienternas välbennande. Det finns datorstödda metoder som kan upptäcka sjukdomen med hjälp av högkvalitativa hjärnskanningar. Dessa typer av skanningar är mycket sällsynta i den kliniska vardagen och därfor ar de metoderna inte tillämpliga for kliniskt bruk. Denna rapport utforskar metoder for att upptäcka Alzheimers sjukdom baserade på deformationsfält av hjärnskanningar. Detta har fördelen att vara robust för intensitetfel och därmed tillämpligt på hjarnskanningar av lägre kvalitet. Metoderna testades med lågkvalitet MRI hjarnskanningar med en skivtjocklek pa 5,5 mm. Tillämpning av en "morphable" modell, som fångar den generella hjärnformen, gav 94/97/92 noggrannhet/känslighet/specificitet för klassifikation av sjuka och friska hjärnor. Detta ar jämförbart med andra metoder som använder högkvalitativa bilder. Detta resultat antyder att det kan vara möjligt att använda metoder baserade pa deformationsfält i forskning med kliniska data, och ger även möjligheten for klinisk användning.
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Baker, K. Adam. "Neural transplantation in the rat model of Parkinson's disease." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0021/MQ57270.pdf.
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Vargas, JoseÌ Danilo. "Model organisms and human disease : from kyphoscoliosis to neurodegeneration." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275381.
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Gould, David James. "Leucocyte recruitment in a model of allergic airways disease." Thesis, University of Southampton, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384947.
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Varley, John Graeme. "Development of a model of allergic airways disease A." Thesis, University of Southampton, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385226.
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Tucker, Lawrence Maskew. "Neural transplantation in an animal model for Huntington's disease." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362863.
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Sinclair, Simon Rupert. "Improving nigral grafts in a model of Parkinson's disease." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624900.
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Farooq, Muhammad. "Use of Drosophila melanogaster to model ovine prion disease." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610654.
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Michel, Claire Hélène Marie. "Investigating inflammation in a Drosophila model of Alzheimer's disease." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608998.
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Li, Yuanxi. "Building trajectories through clinical data to model disease progression." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/8404.
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Clinical trials are typically conducted over a population within a defined time period in order to illuminate certain characteristics of a health issue or disease process. These cross-sectional studies provide a snapshot of these disease processes over a large number of people but do not allow us to model the temporal nature of disease, which is essential for modeling detailed prognostic predictions. Longitudinal studies, on the other hand, are used to explore how these processes develop over time in a number of people but can be expensive and time-consuming, and many studies only cover a relatively small window within the disease process. This thesis describes the application of intelligent data analysis techniques for extracting information from time series generated by different diseases. The aim of this thesis is to identify intermediate stages in a disease process and sub-categories of the disease exhibiting subtly different symptoms. It explores the use of a bootstrap technique that fits trajectories through the data generating “pseudo time-series”. It addresses issues including: how clinical variables interact as a disease progresses along the trajectories in the data; and how to automatically identify different disease states along these trajectories, as well as the transitions between them. The thesis documents how reliable time-series models can be created from large amounts of historical cross-sectional data and a novel relabling/latent variable approach has enabled the exploration of the temporal nature of disease progression. The proposed algorithms are tested extensively on simulated data and on three real clinical datasets. Finally, a study is carried out to explore whether we can “calibrate” pseudo time-series models with real longitudinal data in order to improve them. Plausible directions for future research are discussed at the end of the thesis.
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Smith, Edward John. "Establishing a neural progenitor cell model of Huntington's disease." Thesis, King's College London (University of London), 2017. https://kclpure.kcl.ac.uk/portal/en/theses/establishing-a-neural-progenitor-cell-model-of-huntingtons-disease(5bcdd521-e71a-4dcb-b833-971f32576c2a).html.
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Huntington's disease (HD) is caused by the expansion of a CAG repeat in the huntingtin (HTT) gene The R6/2 transgenic mouse model exhibits a rapid onset of Huntington's disease-like phenotypes including neurodegeneration and aggregation of mutant huntingtin protein (mHTT). Neural progenitor cells (NPCs) are a pool of cells with stem cell-like properties and are responsible for self-renewal and differentiation into the cells of the central nervous system and mature brain. In this thesis, NPC lines were established from cells extracted from foetal R6/2 and wildtype mouse embryos and cultured in optimised culture media. NPCs were successfully maintained in a mitotic state as monolayer cultures for multiple passages without effects to karyotype or CAG repeat length. Cultures were differentiated by removal of growth factors, into mixed neurons and glia populations that expressed proteins indicative of mature cell types; neurons showed evidence of synaptophysin expression at junctions between cell neurites, suggesting synaptic functionality and formation of rudimentary neural networks. After differentiation, mHTT aggregation was detectable using immunohistochemistry from 14 days of differentiation in 5% of R6/2 cell nuclei, rising to 20% by 28 days, recapitulating an HD-like phenotype found in vivo. Detection of detergent insoluble mHTT-aggregated protein was also validated via western blotting. Super high resolution cell imaging showed aggregation of mHTT is also present in the cytoplasm. High-content imaging analysis system was performed using the Operetta system to explore morphological differences between WT and R6/2 cultures, as well as within the subset of cells with detectable aggregation. R6/2 nuclei were found to be larger than those of WT cells. Novel compounds known to affect protein aggregation were applied to the cell lines to assess their potential use in screening for approaches to modulation mHTT aggregation. The cells developed in this thesis are a novel and useful complement to the R6/2 mouse; phenotypes observed in vivo can be interrogated at the molecular level in terms of how mHTT protein misfolding and aggregation occur and how this affects cellular function.
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Tse, Yiu Chung. "Glutamate receptors in an animal model of Parkinson's disease." HKBU Institutional Repository, 1999. http://repository.hkbu.edu.hk/etd_ra/226.
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Saijo(Kim), Misa. "Generation of transgenic animal model of hyperthyroid Graves' disease." Kyoto University, 2004. http://hdl.handle.net/2433/147457.
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Yang, Yufeng. "A drosophila melanogaster model of Pink1-associated parkinson's disease /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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Mubayyid, Abdurrahman M. "Parkinson’s Disease Model in vitro and in C. elegans." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/21388.
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Current treatments of Parkinson’s Disease (PD), a neurodegenerative disease affecting voluntary movement, do not target the underlying pathology, focussing on the symptoms instead. The focus of this study was the usage of a protein involved in the earliest known pathology of PD, αsynuclein (αsyn), to conduct preliminary experiments that could determine potential treatments that affect aggregation of αsyn. First, aggregation of αsyn was measured using a commonly used assay for detecting protein aggregation, thioflavin T (ThT) fluorescence assay. Second, Caenorhabditis elegans (C. elegans), nematodes more recently used as a lowcost model for diseases, were treated with αsyn (transgenic species were used overexpressing αsyn in muscle cells and C. elegans were also exogenously exposed to αsyn) and observed for any behavioural changes in movement and bend speed. Treating αsyn with hops, an ingredient used in brewing beer, showed a 53fold reduction in fluorescence in the ThT assays performed. The mechanism in which hops was affecting ThT fluorescence was unclear but the effect, regardless, demonstrates its potential use as a treatment and warrants further study on its effects on αsyn aggregation. C. elegans overexpressing αsyn and exogenously exposed to αsyn showed changes in movement speed compared to untreated populations and this study found that exposure to hops reversed the changes in speed possibly caused by αsyn.
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Mubayyid, Abdurrahman. "Parkinson’s Disease Model in vitro and in C. elegans." Thesis, The University of Sydney, 2018. https://hdl.handle.net/2123/21213.
Full textAbstract:
Current treatments of Parkinson’s Disease (PD), a neurodegenerative disease affecting voluntary movement, do not target the underlying pathology, focussing on the symptoms instead. The focus of this study was the usage of a protein involved in the earliest known pathology of PD, αsynuclein (αsyn), to conduct preliminary experiments that could determine potential treatments that affect aggregation of αsyn. First, aggregation of αsyn was measured using a commonly used assay for detecting protein aggregation, thioflavin T (ThT) fluorescence assay. Second, Caenorhabditis elegans (C. elegans), nematodes more recently used as a lowcost model for diseases, were treated with αsyn (transgenic species were used overexpressing αsyn in muscle cells and C. elegans were also exogenously exposed to αsyn) and observed for any behavioural changes in movement and bend speed. Treating αsyn with hops, an ingredient used in brewing beer, showed a 53fold reduction in fluorescence in the ThT assays performed. The mechanism in which hops was affecting ThT fluorescence was unclear but the effect, regardless, demonstrates its potential use as a treatment and warrants further study on its effects on αsyn aggregation. C. elegans overexpressing αsyn and exogenously exposed to αsyn showed changes in movement speed compared to untreated populations and this study found that exposure to hops reversed the changes in speed possibly caused by αsyn.
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Diamond-Stanic, Maggie Keck. "Diabetic Kidney Disease in the VCD Model of Menopause." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/195657.
Full textAbstract:
Kidney disease is a major complication of diabetes and accounts for one-third of all diabetes-related deaths. Estrogen is considered protective against cardiovascular and non-diabetic renal disease, however it is unclear if this protection extends to diabetes and diabetic kidney disease.To address these questions, we have used a new model of menopause in which repeated daily injections of 4-vinylcyclohexene (VCD) induces gradual ovarian failure in mice. Unlike with ovariectomy, the VCD model preserves the gradual transition into ovarian failure (OF) (modeling perimenopause). Also, following OF, the residual ovarian tissue is retained and secretes androgens, similar to the androgen production by postmenopausal human ovaries.The VCD model of menopause was combined with the streptozotocin (STZ) model of type 1 diabetes, and the development of diabetes and diabetic kidney damage were studied over the subsequent 6 weeks. We observed that blood glucose levels are higher in post-OF diabetic mice compared to cycling diabetic and peri-OF diabetic mice. Renal cell proliferation, an early marker of kidney damage, is increased in post-OF diabetic mice compared to cycling diabetic mice, as measured by expression of proliferating cell nuclear antigen. We also demonstrate that expression of α-smooth muscle actin is increased in post-OF diabetic mice compared to cycling diabetic mice. Five weeks after STZ injection, post-OF diabetic mice had higher rates of urine albumin excretion than cycling diabetic mice.Using real-time PCR, we identified changes in expression between post-OF diabetic and cycling diabetic mice of genes which have previously been associated with diabetic kidney damage. We also show that some of these changes occur in peri-OF diabetic mice as well. Using microarray, we identified 119 new genes which are regulated by the combination of ovarian failure and diabetes in the mouse kidney.These data support our hypothesis that the changes in hormones which occur during the transition into ovarian failure exacerbate the development and progression of diabetic kidney damage in mice. These data also highlight the utility and importance of the VCD model of menopause in the study of diabetic kidney damage.
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Armstrong, Paul. "Associative learning in a mouse model of Alzheimer's disease." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/41014/.
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Alzheimer’s disease (AD) is a progressive neurodegenerative disease defined by severe memory loss and the accumulation of amyloid plaques and neurofibrillary tangles in the brain. The experiments presented in this thesis examined cognitive performance in a well-‐characterised mouse model of AD, the APPswe/PS1dE9 (TG) mouse, at 4-‐5 months old prior to extensive amyloid plaque deposition. The experiments employed were associative learning tasks, which are not often used to measure cognitive performance in classical neuroscience research into neurodegenerative disease. Chapter 1 looked at appetitive Pavlovian cue and context conditioning and extinction, and found some evidence of impaired contextual discrimination during conditioning. Cue conditioning and extinction was found to be intact in the TG mouse model. Chapter 2 looked at appetitive Pavlovian delay and trace conditioning before examining the ability to time the arrival of the unconditioned stimulus (US). No genotype differences were found during delay or trace conditioning; however, TG mice were impaired (lost precision) in their ability to time the arrival of the US during test trials. Chapter 3 examined recognition memory performance, via the spontaneous novel object recognition (sNOR), relative recency (RR) and context priming (CP) tasks, interpreting the results in terms of Wagner’s SOP model of memory. No genotype differences were found in the sNOR or RR tasks, supporting intact stimulus-‐generated priming; however, evidence from Bonardi et al. (2016) and non-‐significant trends in the CP task supported impaired retrieval-generated priming. Chapter 4 looked at the levels of neuro-‐inflammation (microglia) in the cortex, hippocampus and striatum to assess the possible early contribution of inflammation on the development of AD. This chapter reported greater levels of microglia in the hippocampus and striatum of TG mice compared to wild types. Greater microglia clusters were also seen in the cortex and hippocampus of TG mice compared to wild types. The results from this thesis show evidence of impaired cognitive performance, prior to extensive plaque deposition, in associative learning tasks that are not routinely employed in neuroscience research. Further work is required in these learning tasks to establish whether they could be effectively used to diagnose AD at an early stage.
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Mehl, Christopher. "Bayesian Hierarchical Modeling and Markov Chain Simulation for Chronic Wasting Disease." Diss., University of Colorado at Denver, 2004. http://hdl.handle.net/10919/71563.
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In this thesis, a dynamic spatial model for the spread of Chronic Wasting Disease in Colorado mule deer is derived from a system of differential equations that captures the qualitative spatial and temporal behaviour of the disease. These differential equations are incorporated into an empirical Bayesian hierarchical model through the unusual step of deterministic autoregressive updates. Spatial effects in the model are described directly in the differential equations rather than through the use of correlations in the data. The use of deterministic updates is a simplification that reduces the number of parameters that must be estimated, yet still provides a flexible model that gives reasonable predictions for the disease. The posterior distribution generated by the data model hierarchy possesses characteristics that are atypical for many Markov chain Monte Carlo simulation techniques. To address these difficulties, a new MCMC technique is developed that has qualities similar to recently introduced tempered Langevin type algorithms. The methodology is used to fit the CWD model, and posterior parameter estimates are then used to obtain predictions about Chronic Wasting Disease.
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Barrett, Kerry. "Studies on the development of a mouse model of Graves' disease /." Internet access available to MUN users only, 2003. http://collections.mun.ca/u?/theses,156073.
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Watchon, Maxinne. "Investigating disease mechanisms and potential drug treatments in a transgenic zebrafish model of Machado-Joseph disease." Thesis, The University of Sydney, 2019. http://hdl.handle.net/2123/20272.
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Machado-Joseph disease (MJD) is a neurodegenerative disease resulting in the loss of muscle control and coordination. This disease is caused by inheritance of the ATXN3 gene containing an expanded CAG trinucleotide repeat region encoding for the polyglutamine (polyQ) tract in the ataxin-3 protein. Normally, the length of the CAG repeat region is between 12-44 repeats whilst MJD patients harbour >44 repeats. There is no known treatment or cure to prevent disease progression and understanding the mechanisms causing MJD neuropathology are limited. Thus, there are various cell and animal models exploring potential mechanisms of disease and investigating which treatments could ameliorate disease phenotypes. Our team has generated the first transgenic zebrafish model of MJD. Zebrafish are a popular animal model to investigate neurodegeneration due to external development of the embryos, for easy genetic manipulation and observation. The main advantage is the permeability of embryos, allowing for easy absorption of compounds dissolved in their environment. In combination with this, zebrafish embryos develop rapidly, allowing for high throughput drug testing. This thesis aimed to characterise disease phenotypes that develop in this zebrafish model and study these phenotypes to investigate disease mechanisms and potential treatments. Disease phenotypes identified within the zebrafish expressing human polyQ expanded ataxin-3 protein were motor impairment and ataxin-3 positive cleavage fragments. We monitored these phenotypes to explore a number of related pathways, including autophagy and transcription regulation, to understand how these pathways may relate to the development of the disease phenotypes. Finally, we tested whether a variety of small compounds/drugs are protective. The findings of this drug testing provided valuable insight towards the development of a treatment for MJD.
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Atkins, Tracy. "USING MODELING AND SIMULATION TO EVALUATE DISEASE CONTROL MEASURES." Doctoral diss., University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3976.
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This dissertation introduced several issues concerning the analysis of diseases by showing how modeling and simulation could be used to assist in creating health policy by estimating the effects of such policies. The first question posed was how would education, vaccination and a combination of these two programs effect the possible outbreak of meningitis on a college campus. After creating a model representative of the transmission dynamics of meningitis and establishing parameter values characteristic of the University of Central Florida main campus, the results of a deterministic model were presented in several forms. The result of this model was the combination of education and vaccination would eliminate the possibility of an epidemic on our campus. Next, we used simulation to evaluate how quarantine and treatment would affect an outbreak of influenza on the same population. A mathematical model was created specific to influenza on the UCF campus. Numerical results from this model were then presented in tabular and graphical form. The results comparing the simulations for quarantine and treatment show the best course of action would be to enact a quarantine policy on the campus thus reducing the maximum number of infected while increasing the time to reach this peak. Finally, we addressed the issue of performing the analysis stochastically versus deterministically. Additional models were created with the progression of the disease occurring by chance. Statistical analysis was done on the mean of 100 stochastic simulation runs comparing that value to the one deterministic outcome. The results for this analysis were inconclusive, as the results for meningitis were comparable while those for influenza appeared to be different.Ph.D.
Other
Sciences
Modeling and Simulation PhD
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Lai, Suk King. "Molecular biological and neurochemical studies in a Parkinson's disease model." HKBU Institutional Repository, 2001. http://repository.hkbu.edu.hk/etd_ra/289.
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Al, Rawahi Abdul Hakeem Hamood. "Development of Cardiovascular Risk Assessment Model for People with Type 2 Diabetes in Oman." Thesis, Griffith University, 2017. http://hdl.handle.net/10072/368188.
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Type 2 diabetes mellitus (DM) is one of the most common chronic diseases globally, with worldwide prevalence of 8.3%. Due to its long-lasting nature and high risk of complications, the burden of type 2 DM is expected to rise. Patients with type 2 DM have an estimated two-to-six fold higher risk of developing cardiovascular disease (CVD) compared to the general population. Moreover, CVD is considered the leading cause of morbidity and premature mortality in type 2 diabetic patients.
CVD risk assessment tools in general are mathematical models or charts used to estimate the risk of a CVD event in an individual. CVD risk estimation is important to plan the initiation of preventive and therapeutic measures for CVD prevention including anti-lipid, anti-hypertensive and anti-platelet
therapies, as well as to plan appropriate health education. Various professional guidelines for the management of type 2 DM have advocated the use of CVD risk assessment tools to estimate CVD risk among type 2 diabetic patients using traditional CVD risk factors such as hypertension (HTN),
dyslipidemia, high glycosylated hemoglobin (HbA1c), albuminuria, obesity, smoking status, and family history of CVD. However, most of the existing CVD risk assessment tools were derived from Western populations, with very few developed for East Asian populations.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Medical Science
Griffith Health
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Jackson, Joshua D. "Investigating therapeutic strategies in a preclinical model for Alzheimer's disease." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/investigating-therapeutic-strategies-in-a-preclinical-model-for-alzheimeras-disease(47574a22-9623-4c3e-9fa2-bd68a82ffc31).html.
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Alzheimer's disease (AD) is a worldwide, incurable disease, and the most common form of dementia. Numbers of cases are rising, and since its discovery the only approved medications have treated only the symptoms, not the pathological cause. With the cost to society rising, the debilitating nature of the disease and the pressure put on the family members and support network of patients, disease modifying therapies are in dire need. Current models have proven an invaluable tool with which to study certain aspects of the disease and the genetics behind it, however the lack of clinically approved medications in the last 20 years suggests new models are needed. Based on the amyloid cascade hypothesis, this thesis initially characterises two models of β-Amyloid oligomer (Aβo) induced cognitive deficits. Both models are created by ICV injection of soluble Aβo into the brain of rat. The models differ only by the molecular weight of the Aβo 1-42, one, referred to as low molecular weight (LMW) Aβo, with stable dimers, trimers and tetramers, the other, referred to as high molecular weight (HMW) Aβo, consisting of assemblies ranging from ~50 to ~150 kDa. It was found that behavioural deficits were similar between the two, with a robust object recognition deficit, but no working memory deficit. Both models also showed a deficit in the synaptic marker PSD-95; however the LMW Aβo caused a deficit in the frontal cortex, whereas the HMW Aβo caused a hippocampal deficit. The role of the cellular prion protein (PrPC) was explored, by blocking its binding to Aβo with the antibody 6D11. Interestingly the two models showed different results. The HMW Aβo deficits were completely blocked by the 6D11 application, however the LMW Aβo deficits were only partially prevented. Finally, Fasudil, a vasodilator approved in parts of Asia, was used to inhibit Rho-kinase, showing a prevention of the cognitive deficits in the HMW Aβo model. The results of this thesis show the ICV administration of Aβo to be a useful model for investigating the effects of Aβo, provides a platform with which to study the differing effects of Aβo with different oligomeric assemblies, and a model to test therapeutic strategies with relevance to AD.
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Azouz, Mehdi. "Alzheimer's disease neurotoxic peptides : towards a comprehension of their modes of action on model membranes." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0419.
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La maladie d'Alzheimer (MA) est une neuropathologie complexe qui constitue la principale forme de démence chez l'être humain. Étroitement associée au vieillissement, elle se manifeste par une perte progressive de la mémoire et des fonctions cognitives. Avec 30 millions d’individus concernés au niveau mondial et des estimations voyant ce chiffre quadrupler d'ici 2050, elle constitue aujourd’hui une menace sociétale majeure. L’atrophie cérébrale observée chez les patients atteints de la MA est la conséquence d’un long processus de neurodégénérescence qui intervient au niveau moléculaire et s’amorce bien avant l’apparition des symptômes. Deux marqueurs histopathologiques ont été identifiés comme étant associés à ce processus : les plaques séniles, composées du peptide Abêta et les dégénérescences neurofibrillaires constituées de la protéine Tau. Ces deux molécules, considérées comme les protagonistes décisifs du développement de la MA, concentrent les recherches afin de mieux comprendre leurs rôles dans le processus neurodégénératif et pouvoir mettre en place des solutions thérapeutiques, inexistantes à ce jour.Un des axes de recherche majeurs se focalise sur l’interaction de ces peptides avec la membrane plasmique. L’occurrence d’un tel phénomène pourrait potentiellement être en cause dans la mort neuronale s’il s’avérait délétère. Il est donc capital d’étudier en détail ces processus afin d’identifier les facteurs qui pourraient conduire Abêta et Tau à endommager l’intégrité des membranes. De nombreux travaux ont démontré que certains lipides pouvaient promouvoir ces interactions. Cependant, les conclusions sont parfois divergentes et un consensus commun reste à trouver quant à leurs rôles.Ce travail de thèse s’est consacré à l’étude des modes d’action du peptide Abêta et d’un fragment clé de la protéine Tau, le peptide K18, sur des membranes modèles, en se focalisant principalement sur l’influence de certains lipides. Afin d’élucider les mécanismes qui régissent ces phénomènes, les processus de solubilisation membranaires ont dans un premier temps été étudiés avec des molécules amphiphiles bien caractérisées : les détergents. Cette étude a permis d’établir que les phénomènes de solubilisation membranaires peuvent varier en fonction de la composition membranaire et démontrer de la sélectivité.Le cœur du projet était de visualiser les effets des peptides amyloïdes Abêta et K18 sur des modèles membranaires, les bicouches supportées, avec pour principale technique d’investigation la microscopie à force atomique. Elle nous a permis d’observer ces phénomènes in situ, en conditions physiologiques et à l’échelle sub-micrométrique. Nous avons pu montrer que la composition membranaire était un facteur pouvant moduler l’interaction avec Abêta. L'étude établit que les domaines lipidiques favorisent les perturbations membranaires induites par le peptide. Il est proposé que des défauts d'empilement lipidiques aux interfaces de ces domaines agissent comme des sites d'adsorption du peptide, menant à la destruction des membranes. En utilisant la même approche, avec des compositions lipidiques plus en adéquation avec Tau, nous avons pu établir que K18 induisait également des effets de solubilisation en fonction de la nature des lipides dans la membrane et des propriétés qui leurs sont associées.Dans les deux cas, nous montrons que les effets délétères que peuvent induire ces peptides se manifestent par des effets comparables à ceux des détergents et sont dépendants de la composition des membranes. L’agrégation des peptides, qui peut conduire à leur fibrillation, n’a également été mise en évidence qu’en présence de certains lipides.Ce travail de thèse apporte de nouvelles informations sur le caractère décisif de la membrane à pouvoir moduler les interactions avec les peptides Abêta; et K18. Par extension aux membranes cellulaires, ces phénomènes pourraient potentiellement être associés aux processus neurodégénératifs impliqués dans la MAAlzheimer’s disease is a complex neuropathological disorder that constitutes the prime form of dementia. Intimately related to ageing, it is associated to the gradual loss of memory and cognitive functions in individual suffering from the pathology. With nearly 30 million people concerned today, and the alarming trends predicting this figure to increase fourfold by 2050, Alzheimer’s disease will constitute a major burden for our societies in the upcoming decades. The cerebral atrophy occurring within the brain results from slow and progressive neurodegenerative mechanisms triggered many years before the appearance of the first symptoms. Two histopathological markers have been identified as strongly associated to the neurodegeneration: the senile plaques, majorly composed of the amyloid peptide Abeta, and the neurofibrillary tangles, constituted of the abnormally phosphorylated form of Tau protein. These two molecules, hence considered as the main culprits of the disease, are therefore under the spotlight of researchers who try to better understand the respective roles in the neurodegeneration process and uncover therapeutic solutions to a still uncurable disease.One of the promising research axis is focusing on the interplay between these molecules and the plasma membrane as potential interactions could convincingly rationalize the neural cell deaths if they happened to be deleterious. Therefore, investigate these interactions in detail is of primary importance to identify the factors that might drive Abeta and Tau to cause damages on membranes. A strong body of evidences has demonstrated that certain lipids could promote these interactions and are then suspected to be involved into detrimental phenomena. However, numerous results appear to be contradicting and consensual conclusions are still lacking.This PhD was dedicated to the investigation of the effects of Abeta and K18, a key peptide fragment of Tau protein, on membranes with a particular focus on the influence of lipids. The aim of this work was to elucidate the action mechanisms of these peptides.To first comprehend how membrane damages can be induced, we first focused on the solubilising ability of extensively used amphiphile agents: detergents. As a first study, we revealed that the membrane composition and the physicochemical properties of lipids play an important role in driving the solubilisation of the bilayer, a process that can even lead to a selectivity during the lipid extraction.The core part of the project was to visualize the effects of the amyloid peptides Abeta and K18 on supported lipid bilayers as membrane models, using atomic force microscopy as an investigation technique. With its high spatial resolution and its ability to operate in physiological milieu, this approach has shown that the membrane composition could promote membrane disruption induced by Abeta oligomers in a lipid-dependent manner. More importantly, we propose that packing defects at the interface of membrane domains act as adsorption and nucleation sites leading to membrane damages.Using the same strategy, we observed that K18 could also induce solubilisation phenomenon and demonstrated to be sensitive to the aspect of lipid order in membranes.In both cases, we highlighted that these peptides could be detrimental to supported lipid bilayers and that their disruptive abilities, associated to detergent-like mechanisms, were intimately dependent of lipids. We also show that the aggregation, a phenomenon that can lead to the peptides fibrillation can only be triggered in presence of certain lipids.This work provides important insights about the decisive role of membrane composition in modulating interactions with the Abeta and K18. This interplay could constitute one of the numerous factors that promote neurotoxic phenomena, taking part in the complex neurodegenerative processes associated to Alzheimer’s disease