Do β-amyloid (Aβ) deposits in patients with Alzheimer's disease and Down's syndrome grow according to the log-normal model?

The size frequency distributions of diffuse, primitive and classic β- amyloid (Aβ) deposits were studied in single sections of cortical tissue from patients with Alzheimer's disease (AD) and Down's syndrome (DS) and compared with those predicted by the log-normal model. In a sample of brain regions, these size distributions were compared with those obtained by serial reconstruction through the tissue and the data used to adjust the size distributions obtained in single sections. The adjusted size distributions of the diffuse, primitive and classic deposits deviated significantly from a log-normal model in AD and DS, the greatest deviations from the model being observed in AD. More Aβ deposits were observed close to the mean and fewer in the larger size classes than predicted by the model. Hence, the growth of Aβ deposits in AD and DS does not strictly follow the log-normal model, deposits growing to within a more restricted size range than predicted. However, Aβ deposits grow to a larger size in DS compared with AD which may reflect differences in the mechanism of Aβ formation.

Size distribution curves of senile plaques in patients with Alzheimer’s disease: do plaques grow according to the log-normal model?

The size frequency distributions of diffuse, primitive and cored senile plaques (SP) were studied in single sections of the temporal lobe from 10 patients with Alzheimer’s disease (AD). The size distribution curves were unimodal and positively skewed. The size distribution curve of the diffuse plaques was shifted towards larger plaques while those of the neuritic and cored plaques were shifted towards smaller plaques. The neuritic/diffuse plaque ratio was maximal in the 11 – 30 micron size class and the cored/ diffuse plaque ratio in the 21 – 30 micron size class. The size distribution curves of the three types of plaque deviated significantly from a log-normal distribution. Distributions expressed on a logarithmic scale were ‘leptokurtic’, i.e. with excess of observations near the mean. These results suggest that SP in AD grow to within a more restricted size range than predicted from a log-normal model. In addition, there appear to be differences in the patterns of growth of diffuse, primitive and cored plaques. If neuritic and cored plaques develop from earlier diffuse plaques, then smaller diffuse plaques are more likely to be converted to mature plaques.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

Comparative analysis of a moderating and mediating model of stress, appraisal, and coping in Hispanic and non-Hispanic Alzheimer's disease caregivers

This dissertation utilizes a cross-sectional study to examine the phenomenon of caregiving within a theoretically grounded stress, appraisal, and coping model. Hispanic and non-Hispanic caregivers were studied to examine the factors associated with variance in caregiver appraisal, coping, and outcomes of caregiving strain (depression and somatic complaints) and caregiving gain (life satisfaction, mastery, and personal gain). A purposive sampling strategy was used to recruit 204 Alzheimer's disease caregivers in South Florida. A self-report questionnaire was used to collect demographic data, and to measure stress, appraisal, coping, and psychological well-being of caregivers. Regression equations were developed to compare moderating and mediating models of appraisal and coping. Emotion-focused coping skills were found to significantly moderate the effects of stress (F [1,195] = 4.62, p < .05), explaining approximately 21% of the variance in satisfaction was found to moderate the effects of stress (F [1,195] = 7.09; p < .05), explaining approximately 27% of the variance in personal gain and approximately 8% of the variance in life satisfaction (F [1,195] = 4.14; p < .05). Appraisal of Burden was found to significantly mediate the effects of stress, explaining approximately 30% of the variance in somatic complaints (F [1,196] = 31.60; p < .001) and 32% of the variance in depression (F [1,196] = 38.18; p < .001). The results of the analyses indicate that appraisal and coping skills are important variables in the stress process. The results of this study underscore the importance of accounting for positive and negative outcomes in providing a fuller understanding of the stress, appraisal and coping process of Alzheimer's Disease caregivers. ^

Disease and hygiene in the construction of a nation: The public sphere, public space, and the private domain in Buenos Aires, 1871–1910

The maturation of the public sphere in Argentina during the late nineteenth and early twentieth centuries was a critical element in the nation-building process and the overall development of the modern state. Within the context of this evolution, the discourse of disease generated intense debates that subsequently influenced policies that transformed the public spaces of Buenos Aires and facilitated state intervention within the private domains of the city’s inhabitants. Under the banner of hygiene and public health, municipal officials thus Europeanized the nation’s capital through the construction of parks and plazas and likewise utilized the press to garner support for the initiatives that would remedy the unsanitary conditions and practices of the city. Despite promises to the contrary, the improvements to the public spaces of Buenos Aires primarily benefited the porteño elite while the efforts to root out disease often targeted working-class neighborhoods. The model that reformed the public space of Buenos Aires, including its socially differentiated application of aesthetic order and public health policies, was ultimately employed throughout the Argentine Republic as the consolidated political elite rolled out its national program of material and social development.

Multi-impurity adsorption model for modeling crystal purity and shape evolution during crystallization processes in impure media

Peer reviewed

A model for the modular evolution of rna addressing open questions on the origin of life

A main unsolved problem in the RNA world scenario for the origin of life is how a template-dependent RNA polymerase ribozyme emerged from short RNA oligomers generated by random polymerization of ribonucleotides (Joyce and Orgel 2006). Current estimates establish a minimum size about 165 nt long for such a ribozyme (Johnston et al. 2001), a length three to four times that of the longest RNA oligomers obtained by random polymerization on clay mineral surfaces (Huang and Ferris 2003, 2006). To overcome this gap, we have developed a stepwise model of ligation-based, modular evolution of RNA (Briones et al. 2009) whose main conceptual steps are summarized in Figure 1. This scenario has two main advantages with respect to previous hypotheses put forward for the origin of the RNA world: i) short RNA....

RNA Virus Evolution: a Cross-scale, Disease Dynamic Perspective

RNA viruses are an important cause of global morbidity and mortality. The rapid evolutionary rates of RNA virus pathogens, caused by high replication rates and error-prone polymerases, can make the pathogens difficult to control. RNA viruses can undergo immune escape within their hosts and develop resistance to the treatment and vaccines we design to fight them. Understanding the spread and evolution of RNA pathogens is essential for reducing human suffering. In this dissertation, I make use of the rapid evolutionary rate of viral pathogens to answer several questions about how RNA viruses spread and evolve. To address each of the questions, I link mathematical techniques for modeling viral population dynamics with phylogenetic and coalescent techniques for analyzing and modeling viral genetic sequences and evolution. The first project uses multi-scale mechanistic modeling to show that decreases in viral substitution rates over the course of an acute infection, combined with the timing of infectious hosts transmitting new infections to susceptible individuals, can account for discrepancies in viral substitution rates in different host populations. The second project combines coalescent models with within-host mathematical models to identify driving evolutionary forces in chronic hepatitis C virus infection. The third project compares the effects of intrinsic and extrinsic viral transmission rate variation on viral phylogenies.

Drivers of Dengue Within-Host Dynamics and Virulence Evolution

Dengue is an important vector-borne virus that infects on the order of 400 million individuals per year. Infection with one of the virus's four serotypes (denoted DENV-1 to 4) may be silent, result in symptomatic dengue 'breakbone' fever, or develop into the more severe dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS). Extensive research has therefore focused on identifying factors that influence dengue infection outcomes. It has been well-documented through epidemiological studies that DHF is most likely to result from a secondary heterologous infection, and that individuals experiencing a DENV-2 or DENV-3 infection typically are more likely to present with more severe dengue disease than those individuals experiencing a DENV-1 or DENV-4 infection. However, a mechanistic understanding of how these risk factors affect disease outcomes, and further, how the virus's ability to evolve these mechanisms will affect disease severity patterns over time, is lacking. In the second chapter of my dissertation, I formulate mechanistic mathematical models of primary and secondary dengue infections that describe how the dengue virus interacts with the immune response and the results of this interaction on the risk of developing severe dengue disease. I show that only the innate immune response is needed to reproduce characteristic features of a primary infection whereas the adaptive immune response is needed to reproduce characteristic features of a secondary dengue infection. I then add to these models a quantitative measure of disease severity that assumes immunopathology, and analyze the effectiveness of virological indicators of disease severity. In the third chapter of my dissertation, I then statistically fit these mathematical models to viral load data of dengue patients to understand the mechanisms that drive variation in viral load. I specifically consider the roles that immune status, clinical disease manifestation, and serotype may play in explaining viral load variation observed across the patients. With this analysis, I show that there is statistical support for the theory of antibody dependent enhancement in the development of severe disease in secondary dengue infections and that there is statistical support for serotype-specific differences in viral infectivity rates, with infectivity rates of DENV-2 and DENV-3 exceeding those of DENV-1. In the fourth chapter of my dissertation, I integrate these within-host models with a vector-borne epidemiological model to understand the potential for virulence evolution in dengue. Critically, I show that dengue is expected to evolve towards intermediate virulence, and that the optimal virulence of the virus depends strongly on the number of serotypes that co-circulate. Together, these dissertation chapters show that dengue viral load dynamics provide insight into the within-host mechanisms driving differences in dengue disease patterns and that these mechanisms have important implications for dengue virulence evolution.

A small molecule activator of p300/CBP histone acetyltransferase promotes survival and neurite growth in a cellular model of Parkinson’s disease

Parkinson’s disease (PD) is a progressive neurodegenerative disease characterised by motor and non-motor symptoms, resulting from the degeneration of nigrostriatal dopaminergic neurons and peripheral autonomic neurons. Given the limited success of neurotrophic factors in clinical trials, there is a need to identify new small molecule drugs and drug targets to develop novel therapeutic strategies to protect all neurons that degenerate in PD. Epigenetic dysregulation has been implicated in neurodegenerative disorders, while targeting histone acetylation is a promising therapeutic avenue for PD. We and others have demonstrated that histone deacetylase inhibitors have neurotrophic effects in experimental models of PD. Activators of histone acetyltransferases (HAT) provide an alternative approach for the selective activation of gene expression, however little is known about the potential of HAT activators as drug therapies for PD. To explore this potential, the present study investigated the neurotrophic effects of CTPB (N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-6-pentadecyl-benzamide), which is a potent small molecule activator of the histone acetyltransferase p300/CBP, in the SH-SY5Y neuronal cell line. We report that CTPB promoted the survival and neurite growth of the SH-SY5Y cells, and also protected these cells from cell death induced by the neurotoxin 6-hydroxydopamine. This study is the first to investigate the phenotypic effects of the HAT activator CTPB, and to demonstrate that p300/CBP HAT activation has neurotrophic effects in a cellular model of PD.

Model order reduction for parameterized nonlinear evolution equations

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

Balancing related model order reduction applied to linear controlled evolution equations with Lévy Noise

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

A university e-learning system to enhance higher education teaching environments: a model-base innovative service-orientated clouds intensive evolution approach.

The International Conference on Advanced Materials, Structures and Mechanical Engineering 2015 (ICAMSME 2015) was held on May 29-31, Incheon, South-Korea. The conference was attended by scientists, scholars, engineers and students from universities, research institutes and industries all around the world to present on going research activities. This proceedings volume assembles papers from various professionals engaged in the fields of materials, structures and mechanical engineering.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in clouds: A04BPEL3.0 proposal.

Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.