HSCR has been felt to be a polygeneic disease on the basis of an incompletely penetrant sex modified transmission, which may be either autosomal dominant or recessive in different kindred. During the 1990's several of the genes involved in this transmission have come to light. Other genes remain to be discovered.

Essential hypertension is defined as a chronic elevation of blood pressure of unknown cause. Though a definitive trigger for this change in blood pressure has not been established, there is a strong association with an upregulation of sympathetic output from the central nervous system. There are a number of central autonomic nuclei involved in the maintenance of blood pressure, including the brainstem regions of the nucleus tractus solitarii (NTS), caudal ventrolateral medulla (CVLM), rostral ventrolateral medulla (RVLM), the sympathetic preganglionic neurons (SPNs) within the intermediolateral cell column (IML) of the spinal cord, as well as forebrain regions such as the paraventricular nucleus (PVN) of the hypothalamus. Within these centers, a vast number of neurotransmitters have been identified that contribute to the control of blood pressure, including glutamate, angiotensin II, serotonin, neurotensin, neuropeptide Y, opioids and catecholamines. Recognition of the role of nitric oxide (NO) and its multiple influences over the neural control of blood pressure is gaining increasing significance. Nitric oxide is a unique modulatory molecule that acts as a non-conventional neurotransmitter. As NO is a gas with a short half-life of 4 – 6 seconds, its’ synthesising enzyme, nitric oxide synthase (NOS) is often used as a marker of location of production. Once activated, the best-known “receptor” for NO is soluble guanylate cyclase (sGC), which drives the production of cyclic guanosine monophosphate (cGMP). Identifying the presence of cGMP can therefore be used to determine sites receptive to NO. Previous studies examining the role of NO in the central autonomic control of blood pressure have focused predominantly upon application of either excitatory or inhibitory drugs into the key central autonomic regions and assessing pressor or depressor effects. This thesis aims instead to study the neuroanatomical relationship and functional significance of NO and cGMP expression in the brain and spinal cord of a hypertensive and normotensive rat model. In the first experimental chapter (Chapter 3), a comparative neuroanatomical analysis of neuronal NOS expression and its relationship with cGMP in the SPN of mature Spontaneously Hypertensive Rats (SHR) and their controls, Wistar Kyoto (WKY) was undertaken. Fluorescence immunohistochemistry confirmed the expression of nNOS in the majority of SPN located within the IML region of both strains. However, a strain specific anatomical arrangement of SPN cell clusters was evident and while there was no significant difference between the total number of SPN in each strain, there were significantly fewer nNOS positive SPN in the SHR animals. All nNOS positive SPN were found to express cGMP, and a novel subpopulation of nNOS negative, cGMP-positive SPN was identified. These cells were located in the medial edge of the IML SPN cell group. These results suggest that cGMP is a key signalling molecule in SPN, and that a reduced number of nNOS positive SPN in the SHR may be associated with the increase in sympathetic tone seen in essential hypertension. The second experimental chapter (Chapter 4) aimed to determine if reduced numbers of nNOS containing SPN translated into reduced detectable cGMP. The functional significance of cGMP signalling in the two strains was then examined. Based on previous work by our group, it was predicted that reduced nNOS in the SHR would translate into reduced cGMP and that intrathecal administration of exogenous cGMP in the spinal cord would drive a differential pressor response in the two animal strains. Immunohistochemical techniques confirmed that within each SPN, the relative level of cGMP expression was significantly reduced in the SHR when compared to the WKY. Intrathecal application of 8-bromo-cGMP, a drug analogous to cGMP, increased blood pressure in both strains and had a differential and dose dependent effect, causing only a small increase in blood pressure in anaesthetised WKY animals, while driving a significant pressor response in the SHR. This finding raised the novel hypothesis that in the SHR, reduced nNOS expression is not a driver of hypertension, but is instead a protective mechanism limiting the potent pressor effects of cGMP within SPN. The third experimental chapter (Chapter 5) examines the expression of neuronal and inducible isoforms of NOS (nNOS, iNOS) within the RVLM of SHR and WKY rats. Reverse transcription-polymerase chain reaction (RT-PCR) was used to analyse the level of mRNA expression and immunohistochemistry was then used to further analyse protein levels of nNOS. Total RNA was extracted and reverse transcribed from the RVLM of mature male WKY and SHR. Quantitative real-time PCR indicated that relative to WKY, mRNA levels for nNOS was significantly higher in RVLM of the SHR. This was confirmed immunohistochemically. When compared to iNOS, nNOS was expressed at significantly higher levels overall, however there was no difference in iNOS mRNA expression between the two strains. This demonstration of differential expression levels of nNOS and iNOS in the RVLM raises the possibilities that (i) NO production is up-regulated in the RVLM in SHR in response to increased sympathetic activity in order to re-establish homeostatic balance or alternatively that (ii) an alteration in the balance between nNOS and iNOS activity may underlie the genesis of augmented sympathetic vasomotor tone during hypertension. The fourth experimental chapter (Chapter 6) extends the observations in Chapter 5 through examination of the expression of cGMP and sGC within the RVLM. There is strong functional evidence to suggest that NO signalling in the RVLM relies on cGMP as an intracellular signalling molecule and that this pathway is impaired in hypertension. Immunohistochemistry was used to assess cGMP expression as a marker of active NO signalling in the C1 region of the RVLM, again comparing SHR and WKY animals. Fluorescence immunohistochemistry on sections of the RVLM, double labelled for cGMP and either nNOS or phenylethylamine methyl-transferase (PNMT) failed to reveal cGMP positive neurons in the RVLM from aged animals of either strain, despite consistent detection of cGMP immunoreactivity neurons in the nucleus ambiguus from the same or adjacent sections. This was demonstrated both in the presence and absence of the phosphodiesterase inhibitor isobutylmethylxanthine (IBMX) and in young vs. aged animals. In-vitro incubation of RVLM slices in the NO donor DETA-NO or NMDA did not reveal any additional cGMP neuronal staining within the RVLM. In all studies, cGMP was prominent within the vasculature. Soluble guanylate cyclase immunoreactivity was found throughout the RVLM, although it did not co-localise with the PNMT or nNOS neuronal populations. Overall, results suggest that within the RVLM, cGMP is not detectable in the resting state and cannot be elicited by phosphodiesterase inhibition, NMDA receptor stimulation or NO donor application. A short time course of cGMP signalling or degradation not inhibited by the phosphodiesterase inhibitor utilised (IBMX) in the RVLM cannot be excluded. The final experimental chapter (Chapter 7) examines cGMP expression in magnocellular and preautonomic parvocellular neurons of the PVN. Retrograde tracing techniques and immunohistochemistry were used to visualise cGMP immunoreactivity within functionally, neurochemically and topographically defined PVN neuronal populations in Wistar rats. Basal cGMP immunoreactivity was readily observed in the PVN, both in neuronal and vascular profiles. Cyclic GMP immunoreactivity was significantly higher in magnocellular compared to preautonomic neuronal populations. In preautonomic neurons, the level of cGMP expression was independent on their subnuclei location, innervated target or neurochemical phenotype. The data presented in this chapter indicates a highly heterogeneous distribution of basal cGMP levels within the PVN, and supports work by others indicating that constitutive NO inhibitory actions on preautonomic PVN neurons are likely mediated indirectly through activation of interneurons. Summary Together, these studies comprise a detailed analysis of the neuroanatomical expression of NO and its signalling molecule cGMP in key central autonomic regions involved in the regulation of blood pressure. Under resting or basal conditions, the studies demonstrate notable differences in the expression of NO synthesising enzymes between normotensive and hypertensive animals, and correlating changes in the downstream signalling molecule cGMP. In the spinal cord, novel functional differences in cGMP activity were also demonstrated. In the RVLM, although differences in nNOS were demonstrated, cGMP expression could not be readily detected in either the WKY or SHR, while in contrast within the PVN, cGMP was detected in both magnocellular and parvocellular neuronal populations. Conclusion This thesis gives insight into the physiological role of NO and cGMP as mediators of central blood pressure control. The results presented indicate that the NO-cGMP dependent signalling pathway may not be the dominant driver responsible for maintaining high blood pressure in the SHR model of essential hypertension, and that there is no globally consistent pattern of expression, and indeed the role of NO as a mediator of pressor and depressor function may vary between the autonomic regions examined. Further, it is possible that this pathway is only recruited during activation of reflex homeostatic pathways or during times of marked physiological stress, and that the differences we see in basal expression between the normotensive and SHR animals are instead a result of compensatory mechanisms.

Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Stepping into the 21st century, we see more and more evidence of the growing trend towards the amalgamation of cyberspace and the physical world. This trend emerged as computing technologies moved o_ desktops and migrated into aspects of our lives through their ubiquitous presence in the physical world. As these technologies become enmeshed in our daily routines, they begin to `disappear' from our awareness and cease to be thought of as technologies and simply become tools of everyday use. Yet even as they disappear, these technologies afford a new way for us to interact with the environments of everyday life and with the ordinary objects within these environments. The furthering of this vision will require, in many cases, the tools and applications to possess greater levels of autonomy and an awareness of the user's context. As a result, the applications gradually depend more and more for their behaviour on the information (context information) that is relevant to user interactions. However, it is difficult to develop new context-aware applications that take into account the ever-increasing amount of context information. This is because: the context information sources vary not only in their types, but also in their availability in different environments; the developers have to spend significant programming efforts in gathering, pre-processing and managing the context information when designing and developing the new applications; and, the information sources can fail from time to time, resulting in operational disruptions or service degradation. To make such context information easily and widely available for to new context-aware applications, there is a need to provide information provisioning and management at the infrastructure level. This thesis explores the issues and challenges associated with the development of an autonomic middleware system that addresses the problems discussed earlier, with a particular focus on supporting fault-tolerant context information provisioning for multiple applications, providing the support of opportunistic use of the context sources (the sensors) and, maximising overall the system's interoperability for the open, dynamic computing environments (Ubiquitous computing, for example). The research presented in this thesis makes several key contributions. First, it introduces a novel standards-based approach to model heterogeneous information sources and data preprocessing components. Second, it details the design of a standards-based approach for supporting the dynamic composition of context information sources and pre-processing components. This approach plays an important role in supporting fault-tolerant information provisioning from the sensors and the opportunistic use of these sensors. More specifically, it enables any given piece of high-level context information, as required by applications, to be derived via multiple different pre-processing models, resulting in a higher degree of reliability. Third, it describes the design and development of an autonomic context management system (ACoMS), which harnesses the first two contributions above. Finally, the thesis shows how this autonomic context management system can support context-aware routing in wireless mesh networks. These contributions are evaluated through two corresponding case studies. The first is a practical firefighting scenario with three prototypical applications that validate the design and development of ACoMS. The second is an adaptive wireless mesh surveillance camera system that validates the concept of adopting ACoMS as a cross-layer information plane to ease the prototyping and development of new adaptive protocols and systems, and illustrates the needs of adaptive controls at the sensing layer to optimise resource usage.

Autonomic computing holds great promise for software systems of the future, but at the same time poses great challenges for Software Engineering. Autonomic computing research aims to design software systems that self-configure, self-repair, self-optimize and self-protect, so as to reduce software maintenance cost while improving performance. The aim of our research is to develop tool-supported methodologies for designing and operating autonomic systems. Like other researchers in this area, we assume that autonomic system architectures consist of monitoring, analysis/diagnosis, planning, and execution components that define a feedback loop and serve as the basis for system self-management. This thesis proposes an autonomic framework founded on models of requirements and design. This framework defines the normal operation of a software system in terms of models of its requirements (goal models) and/or operation (statechart models). These models determine what to monitor and how to interpret log data in order to diagnose failures. The monitoring component collects and manages log data. The diagnostic component analyzes log data, identifies failures, and pinpoints problematic components. We transform the diagnostic problem into a propositional satisfiability (SAT) problem solvable by off-the-shelf SAT solvers. Log data are preprocessed into a compact propositional encoding that scales well with growing problem size. For repair, our compensation component executes compensation actions to restore the system to an earlier consistent state. The framework repairs failures through reconfiguration when monitoring and diagnosis use requirements. The reconfiguration component selects a best system reconfiguration that contributes most positively to the system's non-functional requirements. It selects a reconfiguration that achieves this while reconfiguring the system minimally. The framework does not currently offer a repair mechanism when monitoring and diagnosis use statecharts. We illustrate our framework with two medium-sized, publicly-available case studies. We evaluate the framework's performance through a series of experiments on randomly generated and progressively larger specifications. The results demonstrate that our approach scales well with problem size, and can be applied to industrial sized software applications.

This thesis explores the physiologically-mediated interactions between children with profound disabilities and their environment. Using a structure inspired by the musical theme and variation compositional form, the concept of using physiological signals to enrich person-environment interaction will be addressed in two themes. The first theme explores how children with profound disabilities can use their physiological signals to interact with their environment. The variations on this theme: 1) appraise the literature and establish that peripheral autonomic nervous system signals can be controlled by mental activities; 2) present an algorithm that classifies an individual’s mental state using patterns of electrodermal activity to an accuracy of over 80%, and; 3) discusses the challenges with and potential solutions to creating an physiologically-based interaction pathway for children with profound disabilities. The second theme explores how physiological signals can be used to assess the effect of the environmental milieu on a child with profound disabilities. The variations on this theme: 1) demonstrate the effects of the built environment on the life activities of a severely disabled individual by developing and evaluating the effects of a custom-tailored computer access technology; 2) illustrate how the physiological signals of profoundly disabled children are influenced by their social environment by studying the effect of Therapeutic Clowns on children in a long-term rehabilitation setting; and 3) illustrate how differential physiological responses to sounds in the environmental milieu can be used to inform and improve voluntary physiologically-mediated person-environment interaction. The coda of the thesis presents a conceptual framework that has the potential to enrich the interaction between profoundly disabled children and their environment, using music generated from physiological signal patterns to modify their environmental milieu, constructs of personhood and their identity.

Autonomic computing holds great promise for software systems of the future, but at the same time poses great challenges for Software Engineering. Autonomic computing research aims to design software systems that self-configure, self-repair, self-optimize and self-protect, so as to reduce software maintenance cost while improving performance. The aim of our research is to develop tool-supported methodologies for designing and operating autonomic systems. Like other researchers in this area, we assume that autonomic system architectures consist of monitoring, analysis/diagnosis, planning, and execution components that define a feedback loop and serve as the basis for system self-management. This thesis proposes an autonomic framework founded on models of requirements and design. This framework defines the normal operation of a software system in terms of models of its requirements (goal models) and/or operation (statechart models). These models determine what to monitor and how to interpret log data in order to diagnose failures. The monitoring component collects and manages log data. The diagnostic component analyzes log data, identifies failures, and pinpoints problematic components. We transform the diagnostic problem into a propositional satisfiability (SAT) problem solvable by off-the-shelf SAT solvers. Log data are preprocessed into a compact propositional encoding that scales well with growing problem size. For repair, our compensation component executes compensation actions to restore the system to an earlier consistent state. The framework repairs failures through reconfiguration when monitoring and diagnosis use requirements. The reconfiguration component selects a best system reconfiguration that contributes most positively to the system's non-functional requirements. It selects a reconfiguration that achieves this while reconfiguring the system minimally. The framework does not currently offer a repair mechanism when monitoring and diagnosis use statecharts. We illustrate our framework with two medium-sized, publicly-available case studies. We evaluate the framework's performance through a series of experiments on randomly generated and progressively larger specifications. The results demonstrate that our approach scales well with problem size, and can be applied to industrial sized software applications.

This thesis explores the physiologically-mediated interactions between children with profound disabilities and their environment. Using a structure inspired by the musical theme and variation compositional form, the concept of using physiological signals to enrich person-environment interaction will be addressed in two themes. The first theme explores how children with profound disabilities can use their physiological signals to interact with their environment. The variations on this theme: 1) appraise the literature and establish that peripheral autonomic nervous system signals can be controlled by mental activities; 2) present an algorithm that classifies an individual’s mental state using patterns of electrodermal activity to an accuracy of over 80%, and; 3) discusses the challenges with and potential solutions to creating an physiologically-based interaction pathway for children with profound disabilities. The second theme explores how physiological signals can be used to assess the effect of the environmental milieu on a child with profound disabilities. The variations on this theme: 1) demonstrate the effects of the built environment on the life activities of a severely disabled individual by developing and evaluating the effects of a custom-tailored computer access technology; 2) illustrate how the physiological signals of profoundly disabled children are influenced by their social environment by studying the effect of Therapeutic Clowns on children in a long-term rehabilitation setting; and 3) illustrate how differential physiological responses to sounds in the environmental milieu can be used to inform and improve voluntary physiologically-mediated person-environment interaction. The coda of the thesis presents a conceptual framework that has the potential to enrich the interaction between profoundly disabled children and their environment, using music generated from physiological signal patterns to modify their environmental milieu, constructs of personhood and their identity.

The increased complexity, heterogeneity and the dynamism of networked systems and applications make current configuration and management tools to be ineffective. A new paradigm to dynamically configure and manage large-scale complex and heterogeneous networked systems is critically needed. In this dissertation, we present a self configuration paradigm based on the principles of autonomic computing that can handle efficiently complexity, dynamism and uncertainty in configuring networked systems and their applications. Our approach is based on making any resource/application to operate as an Autonomic Component (that means, it can be self-configured, self-healed, self-optimized and self-protected) by using two software modules: Component Management Interface (CMI) to specify the configuration and operational policies associated with each component and Component Runtime Manager (CRM) that manages the component configurations and operations using the policies defined in CMI. We use several configuration metrics (adaptability, complexity, latency, scalability, overhead, and effectiveness) to evaluate the effectiveness of our self-configuration approach when compared to other configuration techniques. We have used our approach to dynamically configure four systems: Automatic IT system management, Dynamic security configuration of networked systems, Self-management of data backup and disaster recovery system and Automatic security patches download and installation on a large scale test bed. Our experimental results showed that by applying our self-configuration approach, the initial configuration time, the initial configuration complexity and the dynamic configuration complexity can be reduced significantly. For example, the configuration time for security patches download and installation on nine machines is reduced to 4399 seconds from 27193 seconds. Furthermore our system provides most adaptability (e.g., 100% for Snort rule set configuration) comparing to hard coded approach (e.g., 22% for Snort rule set configuration) and can improve the performance of managed system greatly. For example, in data backup and recovery system, our approach can reduce the total cost by 54.1% when network bandwidth decreases. In addition, our framework is scalable and imposes very small overhead (less than 1%) on the managed system.

Following spinal cord injury (SCI), up to 70% of patients develop a condition known as autonomic dysreflexia (AD). This study investigates the use of Pregabalin as a preemptive treatment to mitigate the development of AD following SCI in an animal model. Saline-treated and dPGB rats (first Pregabalin treatment 7 days post-SCI) demonstrated typical signs of AD, with mean arterial pressure (MAP) increases of 23.5% and 27.4% respectively, following colon distension. In contrast, iPGB animals (first Pregabalin treatment 1 hour post-SCI) had MAP increases of 14.6%; significantly lower than saline-treated animals. Additionally, iPGB animals had significantly lower urine volumes than saline-treated animals on days 9 and 10 post-SCI, indicating a more rapid return of spontaneous bladder voiding. It was concluded that only treatment with Pregabalin immediately following SCI can alleviate large increases in blood pressure that accompany AD episodes. Immunostaining for substance P revealed a significantly higher density in both the dorsal horn and central autonomic area in iPGB animals when compared to saline-treated and uninjured animals, indicating a possible mechanism of sympathetic inhibition following iPGB treatment.