A general method to determine sampling windows for nonlinear mixed effects models with an application to population pharmacokinetic studies

Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models.

Using process models to support design of airport terminals

The complex design process of airport terminal needs to support a wide range of changes in operational facilities for both usual and unusual/emergency events. Process model describes how activities within a process are connected and also states logical information flow of the various activities. The traditional design process overlooks the necessity of information flow from the process model to the actual building design, which needs to be considered as a integral part of building design. The current research introduced a generic method to obtain design related information from process model to incorporate with the design process. Appropriate integration of the process model prior to the design process uncovers the relationship exist between spaces and their relevant functions, which could be missed in the traditional design approach. The current paper examines the available Business Process Model (BPM) and generates modified Business Process Model(mBPM) of check-in facilities of Brisbane International airport. The information adopted from mBPM then transform into possible physical layout utilizing graph theory.

An authorization framework using building information models

A building information model (BIM) is an electronic repository of structured, three-dimensional data that captures both the physical and dynamic functional characteristics of a facility. In addition to its more traditional function as a tool to aid design and construction, a BIM can be used throughout the life cycle of a facility, functioning as a living database that places resources contained within the building in their spatial and temporal context. Through its comprehension of spatial relationships, a BIM can meaningfully represent and integrate previously isolated control and management systems and processes, and thereby provide a more intuitive interface to users. By placing processes in a spatial context, decision-making can be improved, with positive flow-on effects for security and efficiency. In this article, we systematically analyse the authorization requirements involved in the use of BIMs. We introduce the concept of using a BIM as a graphical tool to support spatial access control configuration and management (including physical access control). We also consider authorization requirements for regulating access to the structured data that exists within a BIM as well as to external systems and data repositories that can be accessed via the BIM interface. With a view to addressing these requirements we present a survey of relevant spatiotemporal access control models, focusing on features applicable to BIMs and highlighting capability gaps. Finally, we present a conceptual authorization framework that utilizes BIMs.

Understanding hydrochemical processes using 3D models and hydrochemical facies in Wairau Plain groundwater, Marlborough

Three dimensional models and groundwater quality are combined to better understand and conceptualise groundwater systems in complex geological settings in the Wairau Plain, Marlborough. Hydrochemical facies, which are characteristic of distinct evolutionary pathways and a common hydrologic history of groundwaters, are identified within geological formations to assess natural water-rock interactions, redox potential and human agricultural impact on groundwater quality in the Wairau Plain.

Development of zonal cartilage constructs : effects of chondrocyte subpopulation, compressive stimulation, and culture models

Articular cartilage is a highly resilient tissue located at the ends of long bones. It has a zonal structure, which has functional significance in load-bearing. Cartilage does not spontaneously heal itself when damaged, and untreated cartilage lesions or age-related wear often lead to osteoarthritis (OA). OA is a degenerative condition that is highly prevalent, age-associated, and significantly affects patient mobility and quality of life. There is no cure for OA, and patients usually resort to replacing the biological joint with an artificial prosthesis. An alternative approach is to dynamically regenerate damaged or diseased cartilage through cartilage tissue engineering, where cells, materials, and stimuli are combined to form new cartilage. However, despite extensive research, major limitations remain that have prevented the wide-spread application of tissue-engineered cartilage. Critically, there is a dearth of information on whether autologous chondrocytes obtained from OA patients can be used to successfully generate cartilage tissues with structural hierarchy typically found in normal articular cartilage. I aim to address these limitations in this thesis by showing that chondrocyte subpopulations isolated from macroscopically normal areas of the cartilage can be used to engineer stratified cartilage tissues and that compressive loading plays an important role in zone-dependent biosynthesis of these chondrocytes. I first demonstrate that chondrocyte subpopulations from the superficial (S) and middle/deep (MD) zones of OA cartilage are responsive to compressive stimulation in vitro, and that the effect of compression on construct quality is zone-dependent. I also show that compressive stimulation can influence pericelluar matrix production, matrix metalloproteinase secretion, and cytokine expression in zonal chondrocytes in an alginate hydrogel model. Subsequently, I focus on recreating the zonal structure by forming layered constructs using the alginate-released chondrocyte (ARC) method either with or without polymeric scaffolds. Resulting zonal ARC constructs had hyaline morphology, and expressed cartilage matrix molecules such as proteoglycans and collagen type II in both scaffold-free and scaffold-based approaches. Overall, my findings demonstrate that chondrocyte subpopulations obtained from OA joints respond sensitively to compressive stimulation, and are able to form cartilaginous constructs with stratified organization similar to native cartilage using the scaffold-free and scaffold-based ARC technique. The ultimate goal in tissue engineering is to help provide improved treatment options for patients suffering from debilitating conditions such as OA. Further investigations in developing functional cartilage replacement tissues using autologous chondrocytes will bring us a step closer to improving the quality of life for millions of OA patients worldwide.

Inquiries, empirical research and regulatory failure

The paper reveals that regulatory failure, often chronic, has characterised the regulatory environments of charities across time and locale. The analysis of the primary literature identifies common issues and suggested remedies pertaining to the regulatory failures of charities. These issues may well be appropriate for consideration by the commission and participants given their persistence in various inquiries for nearly four centuries. Such inquiries also considered other issues not directly referred to in this paper, to also include them would exponentially increase the already unwieldy size of this paper.

The roles of the preproghrelin-derived peptides - ghrelin, desacyl ghrelin and obestatin - in prostate cancer

Prostate cancer is the second most common cause of cancer related deaths in Western men. Despite the significant improvements in current treatment techniques, there is no cure for advanced metastatic, castrate-resistant disease. Early detection and prevention of progression to a castrate-resistant state may provide new strategies to improve survival. A number of growth factors have been shown to act in an autocrine/paracrine manner to modulate prostate cancer tumour growth. Our laboratory has previously shown that ghrelin and its receptors (the functional GHS-R1a and the non-functional GHS-R1b) are expressed in prostate cancer specimens and cell lines. We have shown that ghrelin increases cell proliferation in the PC3 and LNCaP prostate cancer cell lines through activation of ERK1/2, suggesting that ghrelin could regulate prostate cancer cell growth and play a role in the progression of the disease. Ghrelin is a 28 amino-acid peptide hormone, identified to be the natural ligand of the growth hormone secretagogue receptor (GHS-R1a). It is well characterised as a growth hormone releasing and as an orexigenic peptide that stimulates appetite and feeding and regulates energy expenditure and bodyweight. In addition to its orexigenic properties, ghrelin has been shown to play a regulatory role in a number of systems, including the reproductive, immune and cardiovascular systems and may play a role in a number of pathological conditions such as chronic heart failure, anorexia, cachexia, obesity, diabetes and cancer. In cancer, ghrelin and its receptor are expressed in a range of tumours and cancer cell lines and ghrelin has been demonstrated to modulate cell proliferation, apoptosis, migration and invasion in some cell types. The ghrelin gene (GHRL) encodes preproghrelin peptide, which is processed to produce three currently known functional peptides - ghrelin, desacyl ghrelin and obestatin. Prohormone convertases (PCs) have been shown to cleave the preproghrelin peptide into two primary products - the 28 amino acid peptide, ghrelin, and the remaining 117 amino acid C-terminal peptide, C-ghrelin. C-ghrelin can then be further processed to produce the 23 amino acid peptide, obestatin. Ghrelin circulates in two different forms - an octanoylated form (known as ghrelin) and a non-octanoylated form, desacyl ghrelin. The unique post-translational addition of octanoic acid to the serine 3 residue of the propeptide chain to form acylated ghrelin is catalysed by ghrelin O-acyltransferase (GOAT). This modification is necessary for binding of ghrelin to its only known functional receptor, the GHS-R1a. As desacyl ghrelin cannot bind and activate the GHS-R1a, it was initially thought to be an inactive peptide, despite the fact that it circulates at much higher levels than ghrelin. Further research has demonstrated that desacyl ghrelin is biologically active and shares some of the actions of ghrelin, as well as having some opposing and distinct roles. Interestingly, both ghrelin and desacyl ghrelin have been shown to modulate apoptosis, cell differentiation and proliferation in some cell types, and to stimulate cell proliferation through activation of ERK1/2 and PI3K/Akt pathways. The third known peptide product of the ghrelin preprohormone, obestatin, was initially thought to oppose the actions of ghrelin in appetite regulation and food intake and to mediate its effects through the G protein-coupled receptor 39 (GPR39). Subsequent research failed to reproduce the initial findings, however, and the possible anorexigenic effects of obestatin, as well as the identity of its receptor, remain unclear. Obestatin plays some important physiological roles, including roles in improving memory, the inhibition of thirst and anxiety, increased secretion of pancreatic juice, and regulation of cell proliferation, survival, apoptosis and differentiation. Preliminary studies have also shown that obestatin stimulates cell proliferation in some cell types through activation of ERK1/2, Akt and PKC pathways. Overall, however, at the commencement of this PhD project, relatively little was known regarding the functions and mechanisms of action of the preproghrelin-derived functional peptides in modulating prostate cancer cell proliferation. The roles of obestatin, and desacyl ghrelin as potential growth factors had not previously been investigated, and the potential expression and regulation of the preproghrelin processing enzymes, GOAT and prohormone convertases was unknown in prostate cancer cell lines. Therefore, the overall objectives of this study were to: 1. investigate the effects of obestatin on cell proliferation and signaling in prostate cancer cell lines 2. compare the effects of desacyl ghrelin and ghrelin on cell proliferation and signaling in prostate cancer cell lines 3. investigate whether prostate cancer cell lines possess the necessary enzymatic machinery to produce ghrelin and desacyl ghrelin and if these peptides can regulate GOAT expression Our laboratory has previously shown that ghrelin stimulates cell proliferation in the PC3 and LNCaP prostate cancer cell line through activation of the ERK1/2 pathway. In this study it has been demonstrated that treatments with either ghrelin, desacyl ghrelin or obestatin over 72 hours significantly increased cell proliferation in the PC3 prostate cancer cell line but had no significant effect in the RWPE-1 transformed normal prostate cell line. Ghrelin (1000nM) stimulated cell proliferation in the PC3 prostate cancer cell line by 31.66 6.68% (p<0.01) with the WST-1 method, and 13.55 5.68% (p<0.05) with the CyQUANT assay. Desacyl ghrelin (1000nM) increased cell proliferation in PC3 cells by 21.73 2.62% (p<0.01) (WST-1), and 15.46 7.05% (p<0.05) (CyQUANT) above untreated control. Obestatin (1000nM) induced a 28.37 7.47% (p<0.01) (WST-1) and 12.14 7.47% (p<0.05) (CyQUANT) significant increase in cell proliferation in the PC3 prostate cancer cell line. Ghrelin and desacyl ghrelin treatments stimulated Akt and ERK phosphorylation across a range of concentrations (p<0.01). Obestatin treatment significantly stimulated Akt, ERK and PKC phosphorylation (p<0.05). Through the use of specific inhibitors, the MAPK inhibitor U0126 and the Akt1/2 kinase inhibitor, it was demonstrated that ghrelin- and obestatin-induced cell proliferation in the PC3 prostate cancer cell line is mediated through activation of ERK1/2 and Akt pathways. Although desacyl ghrelin significantly stimulated Akt and ERK phosphorylation, U0126 failed to prevent desacyl ghrelin-induced cell proliferation suggesting ghrelin and desacyl ghrelin might act through different mechanisms to increase cell proliferation. Ghrelin and desacyl ghrelin have shown a proliferative effect in osteoblasts, pancreatic -cells and cardiomyocytes through activation of ERK1/2 and PI3K/Akt pathways. Here it has been shown that ghrelin and its non-acylated form exert the same function and stimulate cell proliferation in the PC3 prostate cancer cell line through activation of the Akt pathway. Ghrelin-induced proliferation was also mediated through activation of the ERK1/2 pathway, however, desacyl ghrelin seems to stimulate cell proliferation in an ERK1/2-independent manner. As desacyl ghrelin does not bind and activate GHSR1a, the only known functional ghrelin receptor, the finding that both ghrelin and desacyl ghrelin stimulate cell proliferation in the PC3 cell line suggests that these peptides could be acting through the yet unidentified alternative ghrelin receptor in this cell type. Obestatin treatment also stimulated PKC phosphorylation, however, a direct role for this pathway in stimulating cell proliferation could not be proven using available PKC pathway inhibitors, as they caused significant cell death over the extended timeframe of the cell proliferation assays. Obestatin has been shown to stimulate cell proliferation through activation of PKC isoforms in human retinal epithelial cells and in the human gastric cancer cell line KATO-III. We have demonstrated that all of the prostate-derived cell lines examined (PC3, LNCaP, DU145, 22Rv1, RWPE-1 and RWPE-2) expressed GOAT and at least one of the prohormone convertases, which are known to cleave the proghrelin peptide, PC1/3, PC2 and furin, at the mRNA level. These cells, therefore, are likely to possess the necessary machinery to cleave the preproghrelin protein and to produce the mature ghrelin and desacyl ghrelin peptides. In addition to prohormone convertases, the presence of octanoic acid is essential for acylated ghrelin production. In this study octanoic acid supplementation significantly increased cell proliferation in the PC3 prostate cancer cell line by over 20% compared to untreated controls (p<0.01), but surprisingly, not in the DU145, LNCaP or 22Rv1 prostate cancer cell lines or in the RWPE-1 and RWPE-2 prostate-derived cell lines. In addition, we demonstrated that exogenous ghrelin induced a statistically significant two-fold decrease in GOAT mRNA expression in the PC3 cell line (p<0.05), suggesting that ghrelin could pontentially downregulate its own acylation and, therefore, regulate the balance between ghrelin and desacyl ghrelin. This was not observed, however, in the DU145 and LNCaP prostate cancer cell lines. The GOAT-ghrelin system represents a direct link between ingested nutrients and regulation of ghrelin production and the ghrelin/desacyl ghrelin ratio. Regulation of ghrelin acylation is a potentially attractive and desirable tool for the development of better therapies for a number of pathological conditions where ghrelin has been shown to play a key role. The finding that desacyl ghrelin stimulates cell proliferation in the PC3 prostate cancer cell line, and responds to ghrelin in the same way, suggests that this cell line expresses an alternative ghrelin receptor. Although all the cell lines examined expressed both GHS-R1a and GHS-R1b mRNA, it remains uncertain whether these cell lines express the unidentified alternative ghrelin receptor. It is possible that the varied responses seen could be due to the expression of different ghrelin receptors in different cell lines. In addition to GOAT, prohormone convertases and octanoic acid availability may regulate the production of different peptides from the ghrelin preprohormone. The studies presented in this thesis provide significant new information regarding the roles and mechanisms of action of the preproghrelin-derived peptides, ghrelin, desacyl ghrelin and obestatin, in modulating prostate cancer cell line proliferation. A number of key questions remain to be resolved, however, including the identification of the alternative ghrelin/desacyl ghrelin receptor, the identification of the obestatin receptor, a clarification of the signaling mechanisms which mediate cell proliferation in response to obestatin treatment and a better understanding of the regulation at both the gene and post-translational levels of functional peptide generation. Further studies investigating the role of the ghrelin axis using in vivo prostate cancer models may be warranted. Until these issues are determined, the potential for the ghrelin axis, to be recognised as a novel useful target for therapy for cancer or other pathologies will be uncertain.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Quantum models of cognition and decision

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, "contextuality", is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, "entanglement", allows cognitive phenomena to be modelled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light...

Environmental and economic evaluation of N fertilizer rates in a maize crop in Italy : a spatial and temporal analysis using crop models

Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators.