A theoretical and experimental analysis of the no-load air gap magnetic field in squirrel cage induction machines

In induction machines the tooth frequency losses due to permeance variation constitute a signif'icant, portion of the total loss. In order to predict and estimate these losses it, is essential to obtain a clear understanding of the no-load distribution of the air gap magnetic field and the magnitude of flux pulsation in both stator and rotor teeth. The existing theories and methods by which the air gap permeance variation in a doubly slotted structure is calculated are either empirical or restricted. The main objective of this thesis is to obtain a detailed analysis of the no-load air gap magnetic field distribution and the effect of air gap geometry on the magnitude and waveform of the tooth flux pulsation. In this thesis a detaiiled theoretical and experimental analysis of flux distribution not only leads to a better understanding of the distribution of no-load losses but also provides theoretical analysis for calculating the losses with greater accuracy

Meta-analysis of the population and phenotypic expression of CYP2C9/2C19 polymorphism on drug metabolism in different ethnicities

The term "pharmacogenetics" has been defined as the scientific study of inherited factors that affect the human drug response. Many pharmacogenetie studies have been published since 1995 and have focussed on the principal enzyme family involved in drug metabolism, the cytochrome P450 family, particularly cytochrome P4502C9 and 2C19. In order to investigate the pharmacogenetic aspect of pharmacotherapy, the relevant studies describing the association of pharmacogenetic factor(s) in drug responses must be retrieved from existing literature using a systematic review approach. In addition, the estimation of variant allele prevalence for the gene under study between different ethnic populations is important for pharmacogenetic studies. In this thesis, the prevalence of CYP2C9/2C19 alleles between different ethnicities has been estimated through meta-analysis and the population genetic principle. The clinical outcome of CYP2C9/2C19 allelic variation on the pharmacotherapy of epilepsy has been investigated; although many new antiepileptic drugs have been launched into the market, carbamazepine, phenobarbital and phenytoin are still the major agents in the pharmacotherapy of epilepsy. Therefore, phenytoin was chosen as a model AED and the effect of CYP2C9/2C19 genetic polymorphism on phenytoin metabolism was further examined.An estimation of the allele prevalence was undertaken for three CYP2C9/2C19 alleles respectively using a meta-analysis of studies that fit the Hardy-Weinberg equilibrium. The prevalence of CYP2C9*1 is approximately 81%, 96%, 97% and 94% in Caucasian, Chinese, Japanese, African populations respectively; the pooled prevalence of CYP2C19*1 is about 86%, 57%, 58% and 85% in these ethnic populations respectively. However, the studies of association between CYP2C9/2C19 polymorphism and phenytoin metabolism failed to achieve any qualitative or quantitative conclusion. Therefore, mephenytoin metabolism was examined as a probe drug for association between CYP2C19 polymorphism and mephenytoin metabolic ratio. Similarly, analysis of association between CYP2C9 polymorphism and warfarin dose requirement was undertaken.It was confirmed that subjects carrying two mutated CYP2C19 alleles have higher S/R mephenytoin ratio due to deficient CYP2C19 enzyme activity. The studies of warfarin and CYP2C9 polymorphism did not provide a conclusive result due to poor comparability between studies.The genetic polymorphism of drug metabolism enzymes has been studied extensively, however other genetic factors, such as multiple drug resistance genes (MDR) and genes encoding ion channels, which may contribute to variability in function of drug transporters and targets, require more attention in future pharmacogenetic studies of antiepileptic drugs.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

Metabolic and morphological alterations induced by proteolysis-inducing factor from Walker tumour-bearing rats in C2C12 myotubes

BACKGROUND: Patients with advanced cancer suffer from cachexia, which is characterised by a marked weight loss, and is invariably associated with the presence of tumoral and humoral factors which are mainly responsible for the depletion of fat stores and muscular tissue. METHODS: In this work, we used cytotoxicity and enzymatic assays and morphological analysis to examine the effects of a proteolysis-inducing factor (PIF)-like molecule purified from ascitic fluid of Walker tumour-bearing rats (WF), which has been suggested to be responsible for muscle atrophy, on cultured C2C12 muscle cells. RESULTS: WF decreased the viability of C2C12 myotubes, especially at concentrations of 20-25 mug.mL-1. There was an increase in the content of the pro-oxidant malondialdehyde, and a decrease in antioxidant enzyme activity. Myotubes protein synthesis decreased and protein degradation increased together with an enhanced in the chymotrypsin-like enzyme activity, a measure of functional proteasome activity, after treatment with WF. Morphological alterations such as cell retraction and the presence of numerous cells in suspension were observed, particularly at high WF concentrations. CONCLUSION: These results indicate that WF has similar effects to those of proteolysis-inducing factor, but is less potent than the latter. Further studies are required to determine the precise role of WF in this experimental model. © 2008 Yano et al; licensee BioMed Central Ltd.

Small Ubiquitin-related Modifier (SUMO)-1 promotes glycolysis in hypoxia

Under conditions of hypoxia, most eukaryotic cells undergo a shift in metabolic strategy, which involves increased flux through the glycolytic pathway. Although this is critical for bioenergetic homeostasis, the underlying mechanisms have remained incompletely understood. Here, we report that the induction of hypoxia-induced glycolysis is retained in cells when gene transcription or protein synthesis are inhibited suggesting the involvement of additional post-translational mechanisms. Post-translational protein modification by the small ubiquitin related modifier-1 (SUMO-1) is induced in hypoxia and mass spectrometric analysis using yeast cells expressing tap-tagged Smt3 (the yeast homolog of mammalian SUMO) revealed hypoxia-dependent modification of a number of key glycolytic enzymes. Overexpression of SUMO-1 in mammalian cancer cells resulted in increased hypoxia-induced glycolysis and resistance to hypoxia-dependent ATP depletion. Supporting this, non-transformed cells also demonstrated increased glucose uptake upon SUMO-1 overexpression. Conversely, cells overexpressing the de-SUMOylating enzyme SENP-2 failed to demonstrate hypoxia-induced glycolysis. SUMO-1 overexpressing cells demonstrated focal clustering of glycolytic enzymes in response to hypoxia leading us to hypothesize a role for SUMOylation in promoting spatial re-organization of the glycolytic pathway. In summary, we hypothesize that SUMO modification of key metabolic enzymes plays an important role in shifting cellular metabolic strategies toward increased flux through the glycolytic pathway during periods of hypoxic stress. © 2011 by The American Society for Biochemistry and Molecular Biology, Inc.

Population pharmacokinetic and pharmacogenetic analysis of 6-mercaptopurine in paediatric patients with acute lymphoblastic leukaemia

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • The cytotoxic effects of 6-mercaptopurine (6-MP) were found to be due to drug-derived intracellular metabolites (mainly 6-thioguanine nucleotides and to some extent 6-methylmercaptopurine nucleotides) rather than the drug itself. • Current empirical dosing methods for oral 6-MP result in highly variable drug and metabolite concentrations and hence variability in treatment outcome. WHAT THIS STUDY ADDS • The first population pharmacokinetic model has been developed for 6-MP active metabolites in paediatric patients with acute lymphoblastic leukaemia and the potential demographic and genetically controlled factors that could lead to interpatient pharmacokinetic variability among this population have been assessed. • The model shows a large reduction in interindividual variability of pharmacokinetic parameters when body surface area and thiopurine methyltransferase polymorphism are incorporated into the model as covariates. • The developed model offers a more rational dosing approach for 6-MP than the traditional empirical method (based on body surface area) through combining it with pharmacogenetically guided dosing based on thiopurine methyltransferase genotype. AIMS - To investigate the population pharmacokinetics of 6-mercaptopurine (6-MP) active metabolites in paediatric patients with acute lymphoblastic leukaemia (ALL) and examine the effects of various genetic polymorphisms on the disposition of these metabolites. METHODS - Data were collected prospectively from 19 paediatric patients with ALL (n = 75 samples, 150 concentrations) who received 6-MP maintenance chemotherapy (titrated to a target dose of 75 mg m−2 day−1). All patients were genotyped for polymorphisms in three enzymes involved in 6-MP metabolism. Population pharmacokinetic analysis was performed with the nonlinear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance for the active metabolites. RESULTS - The developed model revealed considerable interindividual variability (IIV) in the clearance of 6-MP active metabolites [6-thioguanine nucleotides (6-TGNs) and 6-methylmercaptopurine nucleotides (6-mMPNs)]. Body surface area explained a significant part of 6-TGNs clearance IIV when incorporated in the model (IIV reduced from 69.9 to 29.3%). The most influential covariate examined, however, was thiopurine methyltransferase (TPMT) genotype, which resulted in the greatest reduction in the model's objective function (P < 0.005) when incorporated as a covariate affecting the fractional metabolic transformation of 6-MP into 6-TGNs. The other genetic covariates tested were not statistically significant and therefore were not included in the final model. CONCLUSIONS - The developed pharmacokinetic model (if successful at external validation) would offer a more rational dosing approach for 6-MP than the traditional empirical method since it combines the current practice of using body surface area in 6-MP dosing with a pharmacogenetically guided dosing based on TPMT genotype.

Biosynthesis and analysis of plant oxylipins

The term oxylipin is applied to the generation of oxygenated products of polyunsaturated fatty acids that can arise either through non-enzymatic or enzymatic processes generating a complex array of products, including alcohols, aldehydes, ketones, acids and hydrocarbon gases. The biosynthetic origin of these products has revealed an array of enzymes involved in their formation and more recently a radical pathway. These include lipoxygenases and α-dioxygenase that insert both oxygen atoms in to the acyl chain to initiate the pathways, to specialised P450 monooxygenases that are responsible for their downstream processing. This latter group include enzymes at the branch points such as allene oxide synthase, leading to jasmonate signalling, hydroperoxide lyase, responsible for generating pathogen/pest defensive volatiles and divinyl ether synthases and peroxygenases involved in the formation of antimicrobial compounds. The complexity of the products generated raises significant challenges for their rapid identification and quantification using metabolic screening methods. Here the current developments in oxylipin metabolism are reviewed together with the emerging technologies required to expand this important field of research that underpins advances in plant-pest/pathogen interactions.

The blood perfusion and NADH/FAD content combined analysis in patients with diabetes foot

Skin blood microcirculation and the metabolism activity of tissue were examined on the patients with type 2 diabetes. Laser Doppler flowmetry (LDF) with 1064 nm laser light source and fluorescence spectroscopy (FS) with excitation light of 365 nm and 450 nm have been used to monitor the blood perfusion and the content of coenzymes NADH and FAD. Concluding, the proposed combined LDF and tissue FS approach allows to identify the significant violations in the blood microcirculation and metabolic activity for type 2 diabetes patients.

Cytokine analysis in Atlantic bottlenose dolphins: Molecular characterization of IL-4, IL-6, and IL-10

The health status of wild and captive Atlantic Bottlenose dolphins ( Tersiops truncatis) is difficult to ascertain. Mass strandings of these animals have been attributed to pollutants, as well as bacterial infections. Using human Enzyme Linked Immuno-Assays (ELISA) for immunological cytokines, I measured soluble cytokine levels with respect to their health status. In a retrospective analysis of dolphin sera, there was a trend of higher cytokine levels in “sick” animals. I cultured dolphin lymphocytes in the presence of a mitogen (PHA), a super antigen (Staph-A), Lipopolysaccharide (LPS), and a calcium flux inducer (PMA). Levels of messenger RNA, from these cultured cells, were assayed with Polymerase Chain Reaction (PCR) using primers for the human cytokines IL-2, IL-4, IL-6, IL-10, Tumor Necrosis Factor, and Interferon gamma. Only IL-4, IL-6, and IL-10 messages were obtained, inferring similar nucleotide homology to the human primer sequences. The PCR products were sequenced. Sixteen IL-4 sequences, twelve IL-6 sequences and seven IL-10 sequences were obtained and analyzed. Each cytokine exhibited the same nucleotide sequence in all dolphins examined. There was no difference in the cytokine profile in response to the various stimuli. The derived amino acid composition for each of the dolphin cytokines was used for molecular modeling, which showed that dolphin IL-4, IL-6, and IL-10 were structurally similar to the corresponding proteins of Perissodactyla. ^

Bioinformatic analysis for exploring relationships between genes and gene products

To carry out their specific roles in the cell, genes and gene products often work together in groups, forming many relationships among themselves and with other molecules. Such relationships include physical protein-protein interaction relationships, regulatory relationships, metabolic relationships, genetic relationships, and much more. With advances in science and technology, some high throughput technologies have been developed to simultaneously detect tens of thousands of pairwise protein-protein interactions and protein-DNA interactions. However, the data generated by high throughput methods are prone to noise. Furthermore, the technology itself has its limitations, and cannot detect all kinds of relationships between genes and their products. Thus there is a pressing need to investigate all kinds of relationships and their roles in a living system using bioinformatic approaches, and is a central challenge in Computational Biology and Systems Biology. This dissertation focuses on exploring relationships between genes and gene products using bioinformatic approaches. Specifically, we consider problems related to regulatory relationships, protein-protein interactions, and semantic relationships between genes. A regulatory element is an important pattern or "signal", often located in the promoter of a gene, which is used in the process of turning a gene "on" or "off". Predicting regulatory elements is a key step in exploring the regulatory relationships between genes and gene products. In this dissertation, we consider the problem of improving the prediction of regulatory elements by using comparative genomics data. With regard to protein-protein interactions, we have developed bioinformatics techniques to estimate support for the data on these interactions. While protein-protein interactions and regulatory relationships can be detected by high throughput biological techniques, there is another type of relationship called semantic relationship that cannot be detected by a single technique, but can be inferred using multiple sources of biological data. The contributions of this thesis involved the development and application of a set of bioinformatic approaches that address the challenges mentioned above. These included (i) an EM-based algorithm that improves the prediction of regulatory elements using comparative genomics data, (ii) an approach for estimating the support of protein-protein interaction data, with application to functional annotation of genes, (iii) a novel method for inferring functional network of genes, and (iv) techniques for clustering genes using multi-source data.

Compilation of downward flux observations from sediment trap deployments in the Atlantic Ocean - Contribution to EURO-BASIN's Data integration

We provide a compilation of downward fluxes (total mass, POC, PON, BSiO2, CaCO3, PIC and lithogenic/terrigenous fluxes) from over 6000 sediment trap measurements distributed in the Atlantic Ocean, from 30 degree North to 49 degree South, and covering the period 1982-2011. Data from the Mediterranean Sea are also included. Data were compiled from different sources: data repositories (BCO-DMO, PANGAEA), time series sites (BATS, CARIACO), published scientific papers and/or personal communications from PI's. All sources are specifed in the data set. Data from the World Ocean Atlas 2009 were extracted to provide each flux observation with contextual environmental data, such as temperature, salinity, oxygen (concentration, AOU and percentage saturation), nitrate, phosphate and silicate.

Sedimentation rates and geochemical analysis of surface sediments from the South Atlantic

Extensive investigations of sedimentary barium were performed in the southern South Atlantic in order to assess the reliability of the barium signal in Antarctic sediments as a proxy for paleoproductivity. Maximum accumulation rates of excess barium were calculated for the Antarctic zone south of the polar front where silica accumulates at high rates. The correspondence between barium and opal supports the applicability of barium as a proxy for productivity. Within the Antarctic zone north of today's average sea ice maximum, interglacial vertical rain rates of excess barium are high, with a maximum occurring during the last deglaciation and early Holocene and during oxygen isotope chronozone 5.5. During these periods, the maximum silica accumulation was supposedly located south of the polar front. Glacial paleoproductivity, instead, was low within the Antarctic zone. North of the polar front, significantly higher barium accumulation occurs during glacial times. The vertical rain rates, however, are as high as in the glacial Antarctic zone. Therefore there was no evidence for an increased productivity in the glacial Southern Ocean.

Data compilation on the biological response to ocean acidification: environmental and experimental context of data sets and related literature

The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.

Advanced thermal analysis of microelectronics using spreading resistance models

Thermal analysis of electronic devices is one of the most important steps for designing of modern devices. Precise thermal analysis is essential for designing an effective thermal management system of modern electronic devices such as batteries, LEDs, microelectronics, ICs, circuit boards, semiconductors and heat spreaders. For having a precise thermal analysis, the temperature profile and thermal spreading resistance of the device should be calculated by considering the geometry, property and boundary conditions. Thermal spreading resistance occurs when heat enters through a portion of a surface and flows by conduction. It is the primary source of thermal resistance when heat flows from a tiny heat source to a thin and wide heat spreader. In this thesis, analytical models for modeling the temperature behavior and thermal resistance in some common geometries of microelectronic devices such as heat channels and heat tubes are investigated. Different boundary conditions for the system are considered. Along the source plane, a combination of discretely specified heat flux, specified temperatures and adiabatic condition are studied. Along the walls of the system, adiabatic or convective cooling boundary conditions are assumed. Along the sink plane, convective cooling with constant or variable heat transfer coefficient are considered. Also, the effect of orthotropic properties is discussed. This thesis contains nine chapters. Chapter one is the introduction and shows the concepts of thermal spreading resistance besides the originality and importance of the work. Chapter two reviews the literatures on the thermal spreading resistance in the past fifty years with a focus on the recent advances. In chapters three and four, thermal resistance of a twodimensional flux channel with non-uniform convection coefficient in the heat sink plane is studied. The non-uniform convection is modeled by using two functions than can simulate a wide variety of different heat sink configurations. In chapter five, a non-symmetrical flux channel with different heat transfer coefficient along the right and left edges and sink plane is analytically modeled. Due to the edge cooling and non-symmetry, the eigenvalues of the system are defined using the heat transfer coefficient on both edges and for satisfying the orthogonality condition, a normalized function is calculated. In chapter six, thermal behavior of two-dimensional rectangular flux channel with arbitrary boundary conditions on the source plane is presented. The boundary condition along the source plane can be a combination of the first kind boundary condition (Dirichlet or prescribed temperature) and the second kind boundary condition (Neumann or prescribed heat flux). The proposed solution can be used for modeling the flux channels with numerous different source plane boundary conditions without any limitations in the number and position of heat sources. In chapter seven, temperature profile of a circular flux tube with discretely specified boundary conditions along the source plane is presented. Also, the effect of orthotropic properties are discussed. In chapter 8, a three-dimensional rectangular flux channel with a non-uniform heat convection along the heat sink plane is analytically modeled. In chapter nine, a summary of the achievements is presented and some systems are proposed for the future studies. It is worth mentioning that all the models and case studies in the thesis are compared with the Finite Element Method (FEM).