943 resultados para Little Higgs model
Resumo:
Diarrhoea is one of the leading causes of morbidity and mortality in populations in developing countries and is a significant health issue throughout the world. Despite the frequency and the severity of the diarrhoeal disease, mechanisms of pathogenesis for many of the causative agents have been poorly characterised. Although implicated in a number of intestinal and extra-intestinal infections in humans, Plesiomonas shigelloides generally has been dismissed as an enteropathogen due to the lack of clearly demonstrated virulence-associated properties such as production of cytotoxins and enterotoxins or invasive abilities. However, evidence from a number of sources has indicated that this species may be the cause of a number of clinical infections. The work described in this thesis seeks to resolve this discrepancy by investigating the pathogenic potential of P. shigelloides using in vitro cell models. The focus of this research centres on how this organism interacts with human host cells in an experimental model. Very little is known about the pathogenic potential of P. shigel/oides and its mechanisms in human infections and disease. However, disease manifestations mimic those of other related microorganisms. Chapter 2 reviews microbial pathogenesis in general, with an emphasis on understanding the mechanisms resulting from infection with bacterial pathogens and the alterations in host cell biology. In addition, this review analyses the pathogenic status of a poorly-defined enteropathogen, P. shigelloides. Key stages of pathogenicity must occur in order for a bacterial pathogen to cause disease. Such stages include bacterial adherence to host tissue, bacterial entry into host tissues (usually required), multiplication within host tissues, evasion of host defence mechanisms and the causation of damage. In this study, these key strategies in infection and disease were sought to help assess the pathogenic potential of P. shigelloides (Chapter 3). Twelve isolates of P. shigelloides, obtained from clinical cases of gastroenteritis, were used to infect monolayers of human intestinal epithelial cells in vitro. Ultrastructural analysis demonstrated that P. shigelloides was able to adhere to the microvilli at the apical surface of the epithelial cells and also to the plasma membranes of both apical and basal surfaces. Furthermore, it was demonstrated that these isolates were able to enter intestinal epithelial cells. Internalised bacteria often were confined within vacuoles surrounded by single or multiple membranes. Observation of bacteria within membranebound vacuoles suggests that uptake of P. shigelloides into intestinal epithelial cells occurs via a process morphologically comparable to phagocytosis. Bacterial cells also were observed free in the host cell cytoplasm, indicating that P. shige/loides is able to escape from the surrounding vacuolar membrane and exist within the cytosol of the host. Plesiomonas shigelloides has not only been implicated in gastrointestinal infections, but also in a range of non-intestinal infections such as cholecystitis, proctitis, septicaemia and meningitis. The mechanisms by which P. shigelloides causes these infections are not understood. Previous research was unable to ascertain the pathogenic potential of P. shigel/oides using cells of non-intestinal origin (HEp-2 cells derived from a human larynx carcinoma and Hela cells derived from a cervical carcinoma). However, with the recent findings (from this study) that P. shigelloides can adhere to and enter intestinal cells, it was hypothesised, that P. shigel/oides would be able to enter Hela and HEp-2 cells. Six clinical isolates of P. shigelloides, which previously have been shown to be invasive to intestinally derived Caco-2 cells (Chapter 3) were used to study interactions with Hela and HEp-2 cells (Chapter 4). These isolates were shown to adhere to and enter both nonintestinal host cell lines. Plesiomonas shigelloides were observed within vacuoles surrounded by single and multiple membranes, as well as free in the host cell cytosol, similar to infection by P. shigelloides of Caco-2 cells. Comparisons of the number of bacteria adhered to and present intracellularly within Hela, HEp-2 and Caco-2 cells revealed a preference of P. shigelloides for Caco-2 cells. This study conclusively showed for the first time that P. shigelloides is able to enter HEp-2 and Hela cells, demonstrating the potential ability to cause an infection and/or disease of extra-intestinal sites in humans. Further high resolution ultrastructural analysis of the mechanisms involved in P. shigelloides adherence to intestinal epithelial cells (Chapter 5) revealed numerous prominent surface features which appeared to be involved in the binding of P. shige/loides to host cells. These surface structures varied in morphology from small bumps across the bacterial cell surface to much longer filaments. Evidence that flagella might play a role in bacterial adherence also was found. The hypothesis that filamentous appendages are morphologically expressed when in contact with host cells also was tested. Observations of bacteria free in the host cell cytosol suggests that P. shigelloides is able to lyse free from the initial vacuolar compartment. The vacuoles containing P. shigel/oides within host cells have not been characterised and the point at which P. shigelloides escapes from the surrounding vacuolar compartment has not been determined. A cytochemical detection assay for acid phosphatase, an enzymatic marker for lysosomes, was used to analyse the co-localisation of bacteria-containing vacuoles and acid phosphatase activity (Chapter 6). Acid phosphatase activity was not detected in these bacteria-containing vacuoles. However, the surface of many intracellular and extracellular bacteria demonstrated high levels of acid phosphatase activity, leading to the proposal of a new virulence factor for P. shigelloides. For many pathogens, the efficiency with which they adhere to and enter host cells is dependant upon the bacterial phase of growth. Such dependency reflects the timing of expression of particular virulence factors important for bacterial pathogenesis. In previous studies (Chapter 3 to Chapter 6), an overnight culture of P. shigelloides was used to investigate a number of interactions, however, it was unknown whether this allowed expression of bacterial factors to permit efficient P. shigelloides attachment and entry into human cells. In this study (Chapter 7), a number of clinical and environmental P. shigelloides isolates were investigated to determine whether adherence and entry into host cells in vitro was more efficient during exponential-phase or stationary-phase bacterial growth. An increase in the number of adherent and intracellular bacteria was demonstrated when bacteria were inoculated into host cell cultures in exponential phase cultures. This was demonstrated clearly for 3 out of 4 isolates examined. In addition, an increase in the morphological expression of filamentous appendages, a suggested virulence factor for P. shigel/oides, was observed for bacteria in exponential growth phase. These observations suggest that virulence determinants for P. shigel/oides may be more efficiently expressed when bacteria are in exponential growth phase. This study demonstrated also, for the first time, that environmental water isolates of P. shigelloides were able to adhere to and enter human intestinal cells in vitro. These isolates were seen to enter Caco-2 host cells through a process comparable to the clinical isolates examined. These findings support the hypothesis of a water transmission route for P. shigelloides infections. The results presented in this thesis contribute significantly to our understanding of the pathogenic mechanisms involved in P. shigelloides infections and disease. Several of the factors involved in P. shigelloides pathogenesis have homologues in other pathogens of the human intestine, namely Vibrio, Aeromonas, Salmonella, Shigella species and diarrhoeaassociated strains of Escherichia coli. This study emphasises the relevance of research into Plesiomonas as a means of furthering our understanding of bacterial virulence in general. As well it provides tantalising clues on normal and pathogenic host cell mechanisms.
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Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.
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Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.
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Background The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors. Results This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors. Conclusion This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.
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This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.
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We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.
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A road traffic noise prediction model (ASJ MODEL-1998) has been integrated with a road traffic simulator (AVENUE) to produce the Dynamic areawide Road traffic NoisE simulator-DRONE. This traffic-noise-GIS based integrated tool is upgraded to predict noise levels in built-up areas. The integration of traffic simulation with a noise model provides dynamic access to traffic flow characteristics and hence automated and detailed predictions of traffic noise. The prediction is not only on the spatial scale but also on temporal scale. The linkage with GIS gives a visual representation to noise pollution in the form of dynamic areawide traffic noise contour maps. The application of DRONE on a real world built-up area is also presented.
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This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.
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The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.
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One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.
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Cell-cell and cell-matrix interactions play a major role in tumor morphogenesis and cancer metastasis. Therefore, it is crucial to create a model with a biomimetic microenvironment that allows such interactions to fully represent the pathophysiology of a disease for an in vitro study. This is achievable by using three-dimensional (3D) models instead of conventional two-dimensional (2D) cultures with the aid of tissue engineering technology. We are now able to better address the complex intercellular interactions underlying prostate cancer (CaP) bone metastasis through such models. In this study, we assessed the interaction of CaP cells and human osteoblasts (hOBs) within a tissue engineered bone (TEB) construct. Consistent with other in vivo studies, our findings show that intercellular and CaP cell-bone matrix interactions lead to elevated levels of matrix metalloproteinases, steroidogenic enzymes and the CaP biomarker, prostate specific antigen (PSA); all associated with CaP metastasis. Hence, it highlights the physiological relevance of this model. We believe that this model will provide new insights for understanding of the previously poorly understood molecular mechanisms of bone metastasis, which will foster further translational studies, and ultimately offer a potential tool for drug screening. © 2010 Landes Bioscience.
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The critical factor in determining students' interest and motivation to learn science is the quality of the teaching. However, science typically receives very little time in primary classrooms, with teachers often lacking the confidence to engage in inquiry-based learning because they do not have a sound understanding of science or its associated pedagogical approaches. Developing teacher knowledge in this area is a major challenge. Addressing these concerns with didactic "stand and deliver" modes of Professional Development (PD) has been shown to have little relevance or effectiveness, yet is still the predominant approach used by schools and education authorities. In response to that issue, the constructivist-inspired Primary Connections professional learning program applies contemporary theory relating to the characteristics of effective primary science teaching, the changes required for teachers to use those pedagogies, and professional learning strategies that facilitate such change. This study investigated the nature of teachers' engagement with the various elements of the program. Summative assessments of such PD programs have been undertaken previously, however there was an identified need for a detailed view of the changes in teachers' beliefs and practices during the intervention. This research was a case study of a Primary Connections implementation. PD workshops were presented to a primary school staff, then two teachers were observed as they worked in tandem to implement related curriculum units with their Year 4/5 classes over a six-month period. Data including interviews, classroom observations and written artefacts were analysed to identify common themes and develop a set of assertions related to how teachers changed their beliefs and practices for teaching science. When teachers implement Primary Connections, their students "are more frequently curious in science and more frequently learn interesting things in science" (Hackling & Prain, 2008). This study has found that teachers who observe such changes in their students consequently change their beliefs and practices about teaching science. They enhance science learning by promoting student autonomy through open-ended inquiries, and they and their students enhance their scientific literacy by jointly constructing investigations and explaining their findings. The findings have implications for teachers and for designers of PD programs. Assertions related to teaching science within a pedagogical framework consistent with the Primary Connections model are that: (1) promoting student autonomy enhances science learning; (2) student autonomy presents perceived threats to teachers but these are counteracted by enhanced student engagement and learning; (3) the structured constructivism of Primary Connections resources provides appropriate scaffolding for teachers and students to transition from didactic to inquiry-based learning modes; and (4) authentic science investigations promote understanding of scientific literacy and the "nature of science". The key messages for designers of PD programs are that: (1) effective programs model the pedagogies being promoted; (2) teachers benefit from taking the role of student and engaging in the proposed learning experiences; (3) related curriculum resources foster long-term engagement with new concepts and strategies; (4) change in beliefs and practices occurs after teachers implement the program or strategy and see positive outcomes in their students; and (5) implementing this study's PD model is efficient in terms of resources. Identified topics for further investigation relate to the role of assessment in providing evidence to support change in teachers' beliefs and practices, and of teacher reflection in making such change more sustainable.