Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via cal- culation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases,the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN : decoys are able to block binding sites on PTEN mRNAs, thereby educing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations

Authorisation management in business process environments: An authorisation model and a policy model

This thesis provides two main contributions. The first one is BP-TRBAC, a unified authorisation model that can support legacy systems as well as business process systems. BP-TRBAC supports specific features that are required by business process environments. BP-TRBAC is designed to be used as an independent enterprise-wide authorisation model, rather than having it as part of the workflow system. It is designed to be the main authorisation model for an organisation. The second contribution is BP-XACML, an authorisation policy language that is designed to represent BPM authorisation policies for business processes. The contribution also includes a policy model for BP-XACML. Using BP-TRBAC as an authorisation model together with BP-XACML as an authorisation policy language will allow an organisation to manage and control authorisation requests from workflow systems and other legacy systems.

An N-ethyl-n-nitrosourea induced corticotropin-releasing hormone promoter mutation provides a mouse model for endogenous glucocorticoid excess

Cushing's syndrome, which is characterized by excessive circulating glucocorticoid concentrations, maybe due to ACTH-dependent or -independent causes that include anterior pituitary and adrenal cortical tumors, respectively. ACTH secretion is stimulated by CRH, and we report a mouse model for Cushing's syndrome due to an N-ethyl-N-nitrosourea (ENU) induced Crh mutation at -120 bp of the promoter region, which significantly increased luciferase reporter activity and was thus a gain-of-function mutation. Crh -120/+ mice, when compared with wild-type littermates, had obesity, muscle wasting, thin skin, hair loss, and elevated plasma and urinary concentrations of corticosterone. In addition, Crh-120/+ mice had hyperglycemia, hyperfructosaminemia, hyperinsulinemia, hypercholesterolemia, hypertriglyceridemia, and hyperleptinemia but normal adiponectin. Crh -120/+ mice also had low bone mineral density, hypercalcemia, hypercalciuria, and decreased concentrations of plasma PTH and osteocalcin. Bone histomorphometry revealed Crh-120/+ mice to have significant reductions in mineralizing surface area, mineral apposition, bone formation rates, osteoblast number, and the percentage of corticoendosteal bone covered by osteoblasts, which was accompanied by an increase in adipocytes in the bone marrow. Thus, a mouse model for Cushing's syndrome has been established, and this will help in further elucidating the pathophysiological effects of glucocorticoid excess and in evaluating treatments for corticosteroid-induced osteoporosis.