GDNF Receptors: Veterans and Novices

Neurotrophic factors play essential role in the development and functioning of the nervous system and other organs. Glial cell line-Derived Neurotrophic Factor (GDNF) family ligands (GFLs) are of particular interest because they promote the survival of dopaminergic neurons in vitro, in Parkinson s disease animal models and in patients. GDNF is also a potent survival factor for the central motoneurons and thus is considered as a potential lead for the treatment of amyotrophic lateral sclerosis. The survival promoting receptor complex for GFLs consists of a ligand-specific co-receptor, GFRα and a signal transducing module, receptor tyrosine kinase RET. At least GDNF and persephin, a GFL, have established functions outside central nervous system. GDNF is crucial for enteric nervous system and kidney development as well as for spermatogenesis. Persephin controls calcitonin secretion. Communication between cells often occurs in the extracellular matrix (ECM), a meshwork, which is secreted and deposited by the cells and is mainly composed of fibrillar proteins and polymerized sugars. We evaluated the relationship between GFLs and extracellular matrix components and demonstrated that three GFLs - GDNF, neurturin and artemin bind heparan sulfates with nanomolar affinities. The fourth member of the family - persephin binds these polysaccharides thousand times less tightly. GDNF, neurturin and artemin also bind with high affinity to heparan sulfate proteoglycan (HSPG) isolated from the nervous system, syndecan-3. GDNF signals through HSPGs, evoking Src family kinase activation. This signaling induces cell spreading, hippocampal neurite outgrowth in vitro and cellular migration. Specifically, GDNF signaling through syndecan-3 is important for embryonic cortical neuron migration. Syndecan-3-deficient mice, similarly to mice lacking GDNF, have less GABAergic neurons in their cortex, as compared to the wild-type mice. This fact provides indirect evidence that GDNF interaction with syndecan-3 is important for cortical brain development. Noteworthy, in non-neuronal tissues GFLs may signal via other syndecans. We also present the structural model for a GDNF co-receptor, GFRα1. The X-ray structure of the GFRα1 domain 3 was solved with 1.8 Å resolution, revealing a new protein fold. Later we also solved the structure of the truncated GFRα1 in the complex with GDNF and this model was confirmed by site-directed mutagenesis. In summary, our work contributed to the structural characterization of GFRα-based receptor complex and revealed a new receptor for GDNF, neurturin and artemin the HSPG syndecan-3. This information is critically important for the development of GFRα/RET agonists for the treatment of neurodegenerative diseases.

Unravelling Molecular and Cellular Disease Mechanisms in Infantile Neuronal Ceroid Lipofuscinosis (INCL)

Studying neurodegeneration provides an opportunity to gain insights into normal cell physiology, and not just pathophysiology. In this thesis work the focus is on Infantile Neuronal Ceroid Lipofuscinosis (INCL). It is a recessively inherited lysosomal storage disorder. The disease belongs to the neuronal ceroid lipofuscinoses (NCLs), a group of common progressive neurodegenerative diseases of the childhood. Characteristic accumulation of autofluorescent storage material is seen in most tissues but only neurons of the central nervous system are damaged and eventually lost during the course of the disease leaving most other cell types unaffected. The disease is caused by mutations in the CLN1 gene, but the physiological function of the corresponding protein the palmitoyl protein thioesterase (PPT1) has remained elusive. The aim of this thesis work was to shed light on the molecular and cell biological mechanisms behind INCL. This study pinpointed the localization of PPT1 in axonal presynapses of neurons. It also established the role of PPT1 in early neuronal maturation as well as importance in mature neuronal synapses. This study revealed an endocytic defect in INCL patient cells manifesting itself as delayed trafficking of receptor and non-receptor mediated endocytic markers. Furthermore, this study was the first to connect the INCL storage proteins the sphingolipid activator proteins (SAPs) A and D to pathological events on the cellular level. Abnormal endocytic processing and intracellular re-localization was demonstrated in patient cells and disease model knock-out mouse neurons. To identify early affected cellular and metabolic pathways in INCL, knock-out mouse neurons were studied by global transcript profiling and functional analysis. The gene expression analysis revealed changes in neuronal maturation and cell communication strongly associated with the regulated secretory system. Furthermore, cholesterol metabolic pathways were found to be affected. Functional studies with the knock-out mouse model revealed abnormalities in neuronal maturation as well as key neuronal functions including abnormalities in intracellular calcium homeostasis and cholesterol metabolism. Together the findings, introduced in this thesis work, support the essential role of PPT1 in developing neurons as well as synaptic sites of mature neurons. Results of this thesis also elucidate early events in INCL pathogenesis revealing defective pathways ultimately leading to the neurodegenerative process. These results contribute to the understanding of the vital physiological function of PPT1 and broader knowledge of common cellular mechanisms behind neurodegeneration. These results add to the knowledge of these severe diseases offering basis for new approaches in treatment strategies.

Buckling, stiffening, and negative dissipation in the dynamics of a biopolymer in an active medium

We present a generic theory for the dynamics of a stiff filament under tension, in an active medium with orientational correlations, such as a microtubule in contractile actin. In sharp contrast to the case of a passive medium, we find the filament can stiffen, and possibly oscillate or buckle, depending on both the contractile or tensile nature of the activity and the filament-medium anchoring interaction. We also demonstrate a strong violation of the fluctuation-dissipation (FD) relation in the effective dynamics of the filament, including a negative FD ratio. Our approach is also of relevance to the dynamics of axons, and our model equations bear a remarkable formal similarity to those in recent work [Martin P, Hudspeth AJ, Juelicher F (2001) Proc Natl Acad Sci USA 98: 14380-14385] on auditory hair cells. Detailed tests of our predictions can be made by using a single filament in actomyosin extracts or bacterial suspensions.

Spiral-Wave Turbulence and Its Control in the Presence of Inhomogeneities in Four Mathematical Models of Cardiac Tissue

Regular electrical activation waves in cardiac tissue lead to the rhythmic contraction and expansion of the heart that ensures blood supply to the whole body. Irregularities in the propagation of these activation waves can result in cardiac arrhythmias, like ventricular tachycardia (VT) and ventricular fibrillation (VF), which are major causes of death in the industrialised world. Indeed there is growing consensus that spiral or scroll waves of electrical activation in cardiac tissue are associated with VT, whereas, when these waves break to yield spiral- or scroll-wave turbulence, VT develops into life-threatening VF: in the absence of medical intervention, this makes the heart incapable of pumping blood and a patient dies in roughly two-and-a-half minutes after the initiation of VF. Thus studies of spiral- and scroll-wave dynamics in cardiac tissue pose important challenges for in vivo and in vitro experimental studies and for in silico numerical studies of mathematical models for cardiac tissue. A major goal here is to develop low-amplitude defibrillation schemes for the elimination of VT and VF, especially in the presence of inhomogeneities that occur commonly in cardiac tissue. We present a detailed and systematic study of spiral- and scroll-wave turbulence and spatiotemporal chaos in four mathematical models for cardiac tissue, namely, the Panfilov, Luo-Rudy phase 1 (LRI), reduced Priebe-Beuckelmann (RPB) models, and the model of ten Tusscher, Noble, Noble, and Panfilov (TNNP). In particular, we use extensive numerical simulations to elucidate the interaction of spiral and scroll waves in these models with conduction and ionic inhomogeneities; we also examine the suppression of spiral- and scroll-wave turbulence by low-amplitude control pulses. Our central qualitative result is that, in all these models, the dynamics of such spiral waves depends very sensitively on such inhomogeneities. We also study two types of control chemes that have been suggested for the control of spiral turbulence, via low amplitude current pulses, in such mathematical models for cardiac tissue; our investigations here are designed to examine the efficacy of such control schemes in the presence of inhomogeneities. We find that a local pulsing scheme does not suppress spiral turbulence in the presence of inhomogeneities; but a scheme that uses control pulses on a spatially extended mesh is more successful in the elimination of spiral turbulence. We discuss the theoretical and experimental implications of our study that have a direct bearing on defibrillation, the control of life-threatening cardiac arrhythmias such as ventricular fibrillation.

Solubilities of Some Chlorophenols in Supercritical CO2 in the Presence and Absence of Cosolvents

The solubilities of three chlorophenols, namely, 4-chlorophenol, 2,4-dichlorophenol, and 2,4,6-trichlorophenol, in supercritical carbon dioxide were determined at temperatures from (308 to 3 18) K in the pressure range of (8.8 to 15.6) MPa. The Solubilities were determined both in the absence of cosolvents and in the presence of two cosolvents, methanol and acetone. The solubilities (in the absence of cosolvents) in mole fraction of 4-chlorophenol, 2,4-dichlorophenol, and 2,4,6-trichlorophenol at 308 K were in the range of (0.0113 to 0.0215), (0.0312 to 0.0645), and (0.008 to 0.0173), respectively. The Solubilities of the chlorophenols followed the order 2,4-dichlorophenol & 4-chlorophenol & phenol & 2,4,6-trichlorophenol & pentachlorophenol. The solubility data were correlated with the Charstil model and with the Mendez-Santiago and Teja model. The overall deviation between the experimental data and the correlated results Was less than 6 % in averaged absolute relative deviation (AARD) for both of the models.

Geomolecular dating and the origin of placental mammals

In modern evolutionary divergence analysis the role of geological information extends beyond providing a timescale, to informing molecular rate variation across the tree. Here I consider the implications of this development. I use fossil calibrations to test the accuracy of models of molecular rate evolution for placental mammals, and reveal substantial misspecification associated with life history rate correlates. Adding further calibrations to reduce dating errors at specific nodes unfortunately tends to transfer underlying rate errors to adjacent branches. Thus, tight calibration across the tree is vital to buffer against rate model errors. I argue that this must include allowing maximum bounds to be tight when good fossil records permit, otherwise divergences deep in the tree will tend to be inflated by the interaction of rate errors and asymmetric confidence in minimum and maximum bounds. In the case of placental mammals I sought to reduce the potential for transferring calibration and rate model errors across the tree by focusing on well-supported calibrations with appropriately conservative maximum bounds. The resulting divergence estimates are younger than others published recently, and provide the long-anticipated molecular signature for the placental mammal radiation observed in the fossil record near the 66 Ma Cretaceous–Paleogene extinction event.

Quench dynamics and defect production in the Kitaev and extended Kitaev models

We study quench dynamics and defect production in the Kitaev and the extended Kitaev models. For the Kitaev model in one dimension, we show that in the limit of slow quench rate, the defect density n∼1/√τ, where 1/τ is the quench rate. We also compute the defect correlation function by providing an exact calculation of all independent nonzero spin correlation functions of the model. In two dimensions, where the quench dynamics takes the system across a critical line, we elaborate on the results of earlier work [K. Sengupta, D. Sen, and S. Mondal, Phys. Rev. Lett. 100, 077204 (2008)] to discuss the unconventional scaling of the defect density with the quench rate. In this context, we outline a general proof that for a d-dimensional quantum model, where the quench takes the system through a d−m dimensional gapless (critical) surface characterized by correlation length exponent ν and dynamical critical exponent z, the defect density n∼1/τmν/(zν+1). We also discuss the variation of the shape and spatial extent of the defect correlation function with both the rate of quench and the model parameters and compute the entropy generated during such a quenching process. Finally, we study the defect scaling law, entropy generation and defect correlation function of the two-dimensional extended Kitaev model.

Proteomic profiling of forskolin-induced differentiated BeWo cells: an in-vitro model of cytotrophoblast differentiation

Placental trophoblastic differentiation is characterized by the fusion of monolayer cytotrophoblasts into syncytiotrophoblasts. During this process of differentiation, several morphological and biochemical changes are known to occur, and this model has been employed to investigate the changes that occur at the gene and protein level during differentiation. Using the sensitive technique of proteomics [two-dimensional gel electrophoresis (2DGE)], changes in protein profile were evaluated in the control and forskolin-induced differentiated cells of trophoblastic choriocarcinoma BeWo cell line. Several proteins were differentially expressed in control and differentiated cells. Four major proteins were up-regulated as assessed by silver staining, and were further characterized as c-h-ras p 21 (phosphorylated), retinoblastoma susceptibility protein I and integrase interactor protein 1. These proteins are known to play an important role in growth arrest of cells, and thus may play a role in initiating the process of differentiation.

Communicative and Anticipatory Decision-making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

Climate change and agriculture: theory and application of mitigation policies

Agriculture’s contribution to climate change is controversial as it is a significant source of greenhouse gases but also a sink of carbon. Hence its economic and technological potential to mitigate climate change have been argued to be noteworthy. However, social profitability of emission mitigation is a result from factors among emission reductions such as surface water quality impact or profit from production. Consequently, to value comprehensive results of agricultural climate emission mitigation practices, these co-effects to environment and economics should be taken into account. The objective of this thesis was to develop an integrated economic and ecological model to analyse the social welfare of crop cultivation in Finland on distinctive cultivation technologies, conventional tillage and conservation tillage (no-till). Further, we ask whether it would be privately or socially profitable to allocate some of barley cultivation for alternative land use, such as green set-aside or afforestation, when production costs, GHG’s and water quality impacts are taken into account. In the theoretical framework we depict the optimal input use and land allocation choices in terms of environmental impacts and profit from production and derive the optimal tax and payment policies for climate and water quality friendly land allocation. The empirical application of the model uses Finnish data about production cost and profit structure and environmental impacts. According to our results, given emission mitigation practices are not self-evidently beneficial for farmers or society. On the contrary, in some cases alternative land allocation could even reduce social welfare, profiting conventional crop cultivation. This is the case regarding mineral soils such as clay and silt soils. On organic agricultural soils, climate mitigation practices, in this case afforestation and green fallow give more promising results, decreasing climate emissions and nutrient runoff to water systems. No-till technology does not seem to profit climate mitigation although it does decrease other environmental impacts. Nevertheless, the data behind climate emission mitigation practices impact to production and climate is limited and partly contradictory. More specific experiment studies on interaction of emission mitigation practices and environment would be needed. Further study would be important. Particularly area specific production and environmental factors and also food security and safety and socio-economic impacts should be taken into account.

The Line Spectral Frequency Model of a Finite-Length Sequence

The line spectral frequency (LSF) of a causal finite length sequence is a frequency at which the spectrum of the sequence annihilates or the magnitude spectrum has a spectral null. A causal finite-length sequencewith (L + 1) samples having exactly L-LSFs, is referred as an Annihilating (AH) sequence. Using some spectral properties of finite-length sequences, and some model parameters, we develop spectral decomposition structures, which are used to translate any finite-length sequence to an equivalent set of AH-sequences defined by LSFs and some complex constants. This alternate representation format of any finite-length sequence is referred as its LSF-Model. For a finite-length sequence, one can obtain multiple LSF-Models by varying the model parameters. The LSF-Model, in time domain can be used to synthesize any arbitrary causal finite-length sequence in terms of its characteristic AH-sequences. In the frequency domain, the LSF-Model can be used to obtain the spectral samples of the sequence as a linear combination of spectra of its characteristic AH-sequences. We also summarize the utility of the LSF-Model in practical discrete signal processing systems.

Modelling and Forecasting Property Rents and Returns (summary section only)

Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.

Managing Project Business Development: an Inter-Organizational and Intra-Organizational Perspective (summary section only)

The driving force behind this study is the gap between the reality of the firms engaged in project business and the available studies covering project management and business process development. Previous studies show that project-based organizations were ‘immature’ in terms of the project-management ‘maturity model’, as few firms were found to be optimizing processes. Even within those, very little attention was paid to combine inter-organizational and intra-organizational perspectives. In this study an effort is made to elaborate some thoughts and views on project management, which interrelate firms’ external and internal activities. In line with the integration, the dissertation uses an approach to the management of project-business interdependencies in the networks of actors, activities and resources. Firstly, the study develops an understanding for inter-organizational perspectives by exploring the complementarities of process activities in the basic development of project business. It presents a framework that is elaborated on the basis of the reciprocal interactions of activities within and outside the organization—thus providing a coherent basis for continuous business-process improvement. In addition, the study presents new tools that can be used to develop project-business processes in each of its functional areas. The research demonstrates how project-business activities can be optimized using the right resources at the right time with the right actors and the right actions. The selected five articles included in this dissertation explain the basic framework for the development of project business. Each paper covers various aspects of inter-organizational and intra-organizational perspectives for project management. The study develops a valuable and procedural model for business-process improvement using the Delphi method that can be used not only in academia but also as a guide for practitioners that takes them through a series of well-defined steps when making informed, consistent and efficient changes to their business processes.

A speech-music discriminator using HILN model based features

We propose a simple speech music discriminator that uses features based on HILN(Harmonics, Individual Lines and Noise) model. We have been able to test the strength of the feature set on a standard database of 66 files and get an accuracy of around 97%. We also have tested on sung queries and polyphonic music and have got very good results. The current algorithm is being used to discriminate between sung queries and played (using an instrument like flute) queries for a Query by Humming(QBH) system currently under development in the lab.

Temperature- and pressure-dependent study of Cl-35 NQR frequency and spin lattice relaxation time in 2,3-dichloroanisole

The temperature and pressure dependence of Cl-35 NQR frequency and spin lattice relaxation time (T-1) were investigated in 2,3-dichloroanisole. Two NQR signals were observed throughout the temperature and pressure range studied. T-1 were measured in the temperature range from 77 to 300 K and from atmospheric pressure to 5 kbar. Relaxation was found to be due to the torsional motion of the molecule and also reorientation f motion of the CH3 group. T-1 versus temperature data were analyzed on the basis of Woessner and Gutowsky model, and the activation energy for the reorientation of the CH3 group was estimated. The temperature dependence of the average torsional lifetimes of the molecules and the transition probabilities were also obtained. NQR frequency shows a nonlinear behavior with pressure, indicating both dynamic and static effects of pressure. The pressure coefficients were observed to be positive for both the lines. A thermodynamic analysis of the data was carried out to determine the constant volume temperature coefficients of the NQR frequency. The variation of spin lattice time with pressure was very small, showing that the relaxation is mainly due to the torsional motions of the molecules. Copyright (C) 2010 John Wiley & Sons, Ltd.