Engineering and Information Technology Collected Works - Research Publications
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ItemFrequency-domain identification of the human controller(SPRINGER, 2012-09)System identification techniques applied to experimental human-in-the-loop data provide an objective test of three alternative control-theoretical models of the human control system: non-predictive control, predictive control, and intermittent predictive control. A two-stage approach to the identification of a single-input single-output control system is used: first, the closed-loop frequency response is derived using the periodic property of the experimental data, followed by the fitting of a parametric model. While this approach is well-established for non-predictive and predictive control, it is here used for the first time with intermittent predictive control. This technique is applied to data from experiments with human volunteers who use one of two control strategies, focusing either on position or on velocity, to manually control a virtual, unstable load which requires sustained feedback to maintain position or low velocity. The results show firstly that the non-predictive controller does not fit the data as well as the other two models, and secondly that the predictive and intermittent predictive controllers provide equally good models which cannot be distinguished using this approach. Importantly, the second observation implies that sustained visual manual control is compatible with intermittent control, and that previous results suggesting a continuous control model for the human control system do not rule out intermittent control as an alternative hypothesis. Thirdly, the parameters identified reflect the control strategy adopted by the human controller.
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ItemIn Silico Investigations of the Anti-Catabolic Effects of Pamidronate and Denosumab on Multiple Myeloma-Induced Bone Disease(PUBLIC LIBRARY SCIENCE, 2012-09-21)It is unclear whether the new anti-catabolic agent denosumab represents a viable alternative to the widely used anti-catabolic agent pamidronate in the treatment of Multiple Myeloma (MM)-induced bone disease. This lack of clarity primarily stems from the lack of sufficient clinical investigations, which are costly and time consuming. However, in silico investigations require less time and expense, suggesting that they may be a useful complement to traditional clinical investigations. In this paper, we aim to (i) develop integrated computational models that are suitable for investigating the effects of pamidronate and denosumab on MM-induced bone disease and (ii) evaluate the responses to pamidronate and denosumab treatments using these integrated models. To achieve these goals, pharmacokinetic models of pamidronate and denosumab are first developed and then calibrated and validated using different clinical datasets. Next, the integrated computational models are developed by incorporating the simulated transient concentrations of pamidronate and denosumab and simulations of their actions on the MM-bone compartment into the previously proposed MM-bone model. These integrated models are further calibrated and validated by different clinical datasets so that they are suitable to be applied to investigate the responses to the pamidronate and denosumab treatments. Finally, these responses are evaluated by quantifying the bone volume, bone turnover, and MM-cell density. This evaluation identifies four denosumab regimes that potentially produce an overall improved bone-related response compared with the recommended pamidronate regime. This in silico investigation supports the idea that denosumab represents an appropriate alternative to pamidronate in the treatment of MM-induced bone disease.
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ItemAqp 9 and Brain Tumour Stem Cells(HINDAWI LTD, 2012)Several studies have implicated the aquaporins (aqp) 1, 4, and 9 in the pathogenesis of malignant brain tumours, suggesting that they contribute to motility, invasiveness, and oedema formation and facilitate metabolism in tumour cells under hypoxic conditions. We have studied the expression of aqp1, 4, and 9 in biopsies from glioblastomas, isolated tumour stem cells grown in a tumoursphere assay and analyzed the progenitor and differentiated cells from these cultures. We have compared these to the situation in normal rat brain, its stem cells, and differentiated cells derived thereof. In short, qPCR in tumour tissue showed presence of aqp1, 4, and 9. In the tumour progenitor population, aqp9 was markedly more highly expressed, whilst in tumour-derived differentiated cells, aqp4 was downregulated. However, immunostaining did not reveal increased protein expression of aqp9 in the tumourspheres containing progenitor cells; in contrast, its expression (both mRNA and protein) was high in differentiated cultures. We, therefore, propose that aquaporin 9 may have a central role in the tumorigenesis of glioblastoma.
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ItemDetect adverse drug reactions for the drug Pravastatin(IEEE, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. ADRs are one of most common causes to withdraw some drugs from market. Prescription event monitoring (PEM) is an important approach to detect the adverse drug reactions. The main problem to deal with this method is how to automatically extract the medical events or side effects from high-throughput medical data, which are collected from day to day clinical practice. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Pravastatin. Major side effects for the drug are detected. The detected ADRs are based on computerized method, further investigation is needed.
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ItemDetect adverse drug reactions for drug Alendronate(IEEE Control Chapter, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Alendronate. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.
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ItemDetect adverse drug reactions for drug Simvastatin(IEEE, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Simvastatin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.
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ItemDetect adverse drug reactions for drug Pioglitazone(IEEE, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Pioglitazone. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.
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ItemDetect adverse drug reactions for drug Atorvastatin(IEEE, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Atorvastatin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.
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ItemDetect Adverse Drug Reactions for Drug Aspirin(IEEE, 2012)Adverse drug reaction (ADR) is widely concerned for public health issue. In this study we propose an original approach to detect the ADRs using feature matrix and feature selection. The experiments are carried out on the drug Aspirin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.
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ItemComparing Data-mining Algorithms Developed for Longitudinal Observational Databases(IEEE, 2012)Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detecting negative side effects. Algorithms mining longitudinal observation databases are not restricted by many of the limitations associated with the more conventional methods that have been developed for spontaneous reporting system databases. In this paper we investigate the robustness of four recently developed algorithms that mine longitudinal observational databases by applying them to The Health Improvement Network (THIN) for six drugs with well document known negative side effects. Our results show that none of the existing algorithms was able to consistently identify known adverse drug reactions above events related to the cause of the drug and no algorithm was superior.