Microtubule-associated protein 1B, a growth-associated and phosphorylated scaffold protein.

Microtubule-associated protein 1B, MAP1B, is one of the major growth associated and cytoskeletal proteins in neuronal and glial cells. It is present as a full length protein or may be fragmented into a heavy chain and a light chain. It is essential to stabilize microtubules during the elongation of dendrites and neurites and is involved in the dynamics of morphological structures such as microtubules, microfilaments and growth cones. MAP1B function is modulated by phosphorylation and influences microtubule stability, microfilaments and growth cone motility. Considering its large size, several interactions with a variety of other proteins have been reported and there is increasing evidence that MAP1B plays a crucial role in the stability of the cytoskeleton and may have other cellular functions. Here we review molecular and functional aspects of this protein, evoke its role as a scaffold protein and have a look at several pathologies where the protein may be involved.

Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

Tax reforms and inequality: theoretical and empirical implications

In this paper we examine the effect of tax policy on the relationship between inequality and growth in a two-sector non-scale model. With non-scale models, the longrun equilibrium growth rate is determined by technological parameters and it is independent of macroeconomic policy instruments. However, this fact does not imply that fiscal policy is unimportant for long-run economic performance. It indeed has important effects on the different levels of key economic variables such as per capita stock of capital and output. Hence, although the economy grows at the same rate across steady states, the bases for economic growth may be different.The model has three essential features. First, we explicitly model skill accumulation, second, we introduce government finance into the production function, and we introduce an income tax to mirror the fiscal events of the 1980¿s and 1990¿s in the US. The fact that the non-scale model is associated with higher order dynamics enables it to replicate the distinctly non-linear nature of inequality in the US with relative ease. The results derived in this paper attract attention to the fact that the non-scale growth model does not only fit the US data well for the long-run (Jones, 1995b) but also that it possesses unique abilities in explaining short term fluctuations of the economy. It is shown that during transition the response of the relative simulated wage to changes in the tax code is rather non-monotonic, quite in accordance to the US inequality pattern in the 1980¿s and early 1990¿s.More specifically, we have analyzed in detail the dynamics following the simulation of an isolated tax decrease and an isolated tax increase. So, after a tax decrease the skill premium follows a lower trajectory than the one it would follow without a tax decrease. Hence we are able to reduce inequality for several periods after the fiscal shock. On the contrary, following a tax increase, the evolution of the skill premium remains above the trajectory carried on by the skill premium under a situation with no tax increase. Consequently, a tax increase would imply a higher level of inequality in the economy

The TRAF-interacting protein (TRIP) is a regulator of keratinocyte proliferation.

The TRAF-interacting protein (TRIP/TRAIP) is a RING-type E3 ubiquitin ligase inhibiting tumor necrosis factor-α (TNF-α)-mediated NF-κB activation. TRIP ablation results in early embryonic lethality in mice. To investigate TRIP function in epidermis, we examined its expression and the effect of TRIP knockdown (KD) in keratinocytes. TRIP mRNA expression was strongly downregulated in primary human keratinocytes undergoing differentiation triggered by high cell density or high calcium. Short-term phorbol-12-myristate-13-acetate (TPA) treatment or inhibition of phosphatidylinositol-3 kinase signaling in proliferative keratinocytes suppressed TRIP transcription. Inhibition by TPA was protein kinase C dependent. Keratinocytes undergoing KD of TRIP expression by lentiviral short-hairpin RNA (shRNA; T4 and T5) had strongly reduced proliferation rates compared with control shRNA. Cell cycle analysis demonstrated that TRIP-KD caused growth arrest in the G1/S phase. Keratinocytes with TRIP-KD resembled differentiated cells consistent with the augmented expression of differentiation markers keratin 1 and filaggrin. Luciferase-based reporter assays showed no increase in NF-κB activity in TRIP-KD keratinocytes, indicating that NF-κB activity in keratinocytes is not regulated by TRIP. TRIP expression was increased by ∼2-fold in basal cell carcinomas compared with normal skin. These results underline the important role of TRIP in the regulation of cell cycle progression and the tight linkage of its expression to keratinocyte proliferation.

Analysis of glial acidic fibrillary protein in the human entorhinal cortex during aging and in Alzheimer's disease.

Glial fibrillary acidic protein, GFAP, is a major intermediate filament protein of glial cells and major cytoskeletal structure in astrocytes. The entorhinal cortex has a key role in memory function and is one of the first brain areas to reveal hallmark structures of Alzheimer's disease and therefore provides an ideal tissue to investigate incipient neurodegenerative changes. Here we have analyzed age- and disease-related occurrence and composition of GFAP in the human entorhinal cortex by using one- and two-dimensional electrophoresis, Western blots and immunocytochemistry combined with confocal microscopy. A novel monoclonal antibody, GF-02, was characterized that mainly reacted with intact GFAP molecules and indicated that more acidic and soluble GFAP forms were also more susceptible to degradation. GFAP and vimentin increased with aging and in Alzheimer's disease (AD). Two-dimensional electrophoresis and Western blots revealed a complex GFAP pattern, both in aging and AD with different modification and degradation forms. Immunohistochemistry indicated that reactive astrocytes mainly accumulated in relation to neurofibrillary tangles and senile plaques in deeper entorhinal cortex layers. GFAP may be used as an additional but not exclusive diagnostic tool in the evaluation of neurodegenerative diseases because its levels change with age and respond to senile plaque and tangle formation.

Empirical determination of the very high energy heavy quark cross section from nonaccelerator data

To cosmic rays incident near the horizon the Earth's atmosphere represents a beam dump with a slant depth reaching 36 000 g cm-2 at 90. The prompt decay of a heavy quark produced by very high energy cosmic ray showers will leave an unmistakable signature in this dump. We translate the failure of experiments to detect such a signal into an upper limit on the heavy quark hadroproduction cross section in the energy region beyond existing accelerators. Our results disfavor any rapid growth of the cross section or the gluon structure function beyond conservative estimates based on perturbative QCD.

Characterization of the expression, regulation and function of Sorting Nexin 9 and Sorting Nexin 18

Summary : Sorting nexin (SNX) family members play important roles in intracellular protein and membrane trafficking, The membrane-tubulating SNX9 protein has been shown to interact with multiple components of the endocytic machinery and to participate in clathrin-mediated endocytosis of cell surface receptors. It has not been investigated if SNX9 may also participate in other protein sorting pathways that involve vesicular transport, specifically the biogenesis of lysosome-related organelles (LROs). Closely related to SNX9 is SNXl8, whose function is largely unknown. In this work, we have characterized the expression of SNX9 and SNXl8 in LRO-containing cells and investigated their role in protein trafficking during the formation of LROs. Our results indicate that SNX9 and SNXl8 are not essential for the formation of LROs, nor for the sorting of melanosomal proteins. We investigated how the level of intracellular SNX9 protein is regulated and found that it is a substrate of the ubiquitin ligase Itch, a member of the NEDD4 family of E3 ubiquitin ligases. Itch ubiquitylates SNX9 and regulates SNX9 levels by enhancing its degradation. Using ? truncated proteins we found that the interaction with SNX9 is mediated by the proline-rich domain of Itch, a domain distinct from the conventional WW recognition domain, and the SH3 domain of SNX9. Interaction with the PRD of Itch is essential for SNX9 ubiquitylation and degradation. We further showed that Itch binding is not affected by tyrosine phosphorylation of SNX9. Using lentivector-mediated siRNA techniques, we found that Itch regulates the level of melanosomal proteins, while knock-down of SNX9 does not alter their level. Interestingly, we revealed that silencing of SNXIS affects the amount of the melanosomal protein Melan-A, but also of SNX9, and that SNXl8 can interact with SNX9. Taken together, our results highlight that the pool of substrates of NEDD4 family E3 ligases extends to proteins containing SH3 domains and provide insight into the potential functions of SNXI8. Résumé : Les membres de la famille des Sorting Nexins (SNX) jouent des rôles importants dans le trafic intracellulaire de protéines et membranes. Il a été démontré que la protéine SNX9, qui génère les tubules membranaires, interagit avec plusieurs composants de la machinerie d'endocytose et participe à l'endocytose des récepteurs de surface mediée par la clathrine. Aucune étude n'a investigué si SNX9 pourrait aussi participer à d'autres voies de trafic de protéines tel que le transport vésiculaire, et plus particulièrement la biogenèse des organites lysosomaux ("lysosome-related organelles", LR©s). SNXl8 est similaire à SNX9, mais sa fonction est largement inconnue. Dans ce travail, nous avons caractérisé l'expression de SNX9 et SNX18 dans des cellules contenants des LROs et investigué leur rôle dans le trafic de protéines pendant la formation des LROS. Nos résultats indiquent que SNX9 et SNXI8 ne sont essentiels ni pour la formation des LR©s, ni pour le trafic de protéines mélanosomales. Nous avons examiné la régulation du niveau intracellulaire de la protéine SNX9 et avons trouvé qu'elle est un substrat de l'ubiquitine ligase Itch, un membre de la famille NEDD4 des ubiquitine ligases E3. Itch ubiquitine SNX9 et régule les niveaux de SNX9 en augmentant sa dégradation. En utilisant des protéines mutées nous avons découvert que l'interaction avec SNX9 est médiée par le domaine riche en proline de Itch, qui est différent du domaine conventionnel de reconnaissance WW, et par le domaine SH3 de SNX9. L'interaction avec le domaine riche en proline de Itch est essentielle pour l'ubiquitination et la dégradation de SNX9. De plus, nous avons montré que cette liaison n'est pas affectée par la phosphorylation des résidus tyrosine de SNX9. En utilisant des vecteurs lentiviraux exprimant des siARN, nous avons trouvé que Itch régule les niveaux de protéines mélanosomales, alors que l'extinction de l'expression de SNX9 ne change pas leurs niveaux. En autre, nous avons révélé que la diminution de SNXl8 affecte le niveau de la protéine mélanosomale Melan-A et de SNX9, et aussi que SNXl8 peut interagir avec SNX9. En résumé, nos résultats démontrent que l'ensemble des substrats de la famille NEDD4 des ubiquitine ligases E3 s'élargit aux protéines contenant des domaines SH3 et ouvrent des perspectives sur les fonctions potentielles de SNXl8.

KCM, a general framework for codon-based model of evolution

With the advancement of high-throughput sequencing and dramatic increase of available genetic data, statistical modeling has become an essential part in the field of molecular evolution. Statistical modeling results in many interesting discoveries in the field, from detection of highly conserved or diverse regions in a genome to phylogenetic inference of species evolutionary history Among different types of genome sequences, protein coding regions are particularly interesting due to their impact on proteins. The building blocks of proteins, i.e. amino acids, are coded by triples of nucleotides, known as codons. Accordingly, studying the evolution of codons leads to fundamental understanding of how proteins function and evolve. The current codon models can be classified into three principal groups: mechanistic codon models, empirical codon models and hybrid ones. The mechanistic models grasp particular attention due to clarity of their underlying biological assumptions and parameters. However, they suffer from simplified assumptions that are required to overcome the burden of computational complexity. The main assumptions applied to the current mechanistic codon models are (a) double and triple substitutions of nucleotides within codons are negligible, (b) there is no mutation variation among nucleotides of a single codon and (c) assuming HKY nucleotide model is sufficient to capture essence of transition- transversion rates at nucleotide level. In this thesis, I develop a framework of mechanistic codon models, named KCM-based model family framework, based on holding or relaxing the mentioned assumptions. Accordingly, eight different models are proposed from eight combinations of holding or relaxing the assumptions from the simplest one that holds all the assumptions to the most general one that relaxes all of them. The models derived from the proposed framework allow me to investigate the biological plausibility of the three simplified assumptions on real data sets as well as finding the best model that is aligned with the underlying characteristics of the data sets. -- Avec l'avancement de séquençage à haut débit et l'augmentation dramatique des données géné¬tiques disponibles, la modélisation statistique est devenue un élément essentiel dans le domaine dé l'évolution moléculaire. Les résultats de la modélisation statistique dans de nombreuses découvertes intéressantes dans le domaine de la détection, de régions hautement conservées ou diverses dans un génome de l'inférence phylogénétique des espèces histoire évolutive. Parmi les différents types de séquences du génome, les régions codantes de protéines sont particulièrement intéressants en raison de leur impact sur les protéines. Les blocs de construction des protéines, à savoir les acides aminés, sont codés par des triplets de nucléotides, appelés codons. Par conséquent, l'étude de l'évolution des codons mène à la compréhension fondamentale de la façon dont les protéines fonctionnent et évoluent. Les modèles de codons actuels peuvent être classés en trois groupes principaux : les modèles de codons mécanistes, les modèles de codons empiriques et les hybrides. Les modèles mécanistes saisir une attention particulière en raison de la clarté de leurs hypothèses et les paramètres biologiques sous-jacents. Cependant, ils souffrent d'hypothèses simplificatrices qui permettent de surmonter le fardeau de la complexité des calculs. Les principales hypothèses retenues pour les modèles actuels de codons mécanistes sont : a) substitutions doubles et triples de nucleotides dans les codons sont négligeables, b) il n'y a pas de variation de la mutation chez les nucléotides d'un codon unique, et c) en supposant modèle nucléotidique HKY est suffisant pour capturer l'essence de taux de transition transversion au niveau nucléotidique. Dans cette thèse, je poursuis deux objectifs principaux. Le premier objectif est de développer un cadre de modèles de codons mécanistes, nommé cadre KCM-based model family, sur la base de la détention ou de l'assouplissement des hypothèses mentionnées. En conséquence, huit modèles différents sont proposés à partir de huit combinaisons de la détention ou l'assouplissement des hypothèses de la plus simple qui détient toutes les hypothèses à la plus générale qui détend tous. Les modèles dérivés du cadre proposé nous permettent d'enquêter sur la plausibilité biologique des trois hypothèses simplificatrices sur des données réelles ainsi que de trouver le meilleur modèle qui est aligné avec les caractéristiques sous-jacentes des jeux de données. Nos expériences montrent que, dans aucun des jeux de données réelles, tenant les trois hypothèses mentionnées est réaliste. Cela signifie en utilisant des modèles simples qui détiennent ces hypothèses peuvent être trompeuses et les résultats de l'estimation inexacte des paramètres. Le deuxième objectif est de développer un modèle mécaniste de codon généralisée qui détend les trois hypothèses simplificatrices, tandis que d'informatique efficace, en utilisant une opération de matrice appelée produit de Kronecker. Nos expériences montrent que sur un jeux de données choisis au hasard, le modèle proposé de codon mécaniste généralisée surpasse autre modèle de codon par rapport à AICc métrique dans environ la moitié des ensembles de données. En outre, je montre à travers plusieurs expériences que le modèle général proposé est biologiquement plausible.

A natural structural variant of the mouse TCR beta-chain displays intrinsic receptor function and antigen specificity.

The Cbeta0 alternate cassette exon is located between the Jbeta1 and Cbeta1 genes in the mouse TCR beta-locus. In T cells with a VDJbeta1 rearrangement, the Cbeta0 exon may be included in TCRbeta transcripts (herein called TCRbeta-Cbeta0 transcripts), potentially inserting an additional 24 aa between the V and C domains of the TCR beta-chain. These TCRbeta splice isoforms may be differentially regulated after Ag activation, because we detected TCRbeta-Cbeta0 transcripts in a high proportion (>60%) of immature and mature T cells having VDJbeta1 rearrangements but found a substantially reduced frequency (<35%) of TCRbeta-Cbeta0 expression among CD8 T cells selected by Ag in vivo. To study the potential activity of the TCRbeta-Cbeta0 splice variant, we cloned full-length TCR cDNAs by single-cell RT-PCR into retroviral expression vectors. We found that the TCRbeta-Cbeta0 splice isoform can function during an early stage of T cell development normally dependent on TCR beta-chain expression. We also demonstrate that T hybridoma-derived cells expressing a TCRbeta-Cbeta0 isoform together with the clonally associated TCR alpha-chain recognize the same cognate peptide-MHC ligand as the corresponding normal alphabetaTCR. This maintenance of receptor function and specificity upon insertion of the Cbeta0 peptide cassette signifies a remarkable adaptability for the TCR beta-chain, and our findings open the possibility that this splice isoform may function in vivo.

The malaria circumsporozoite protein has two functional domains, each with distinct roles as sporozoites journey from mosquito to mammalian host.

Plasmodium sporozoites make a remarkable journey from the mosquito midgut to the mammalian liver. The sporozoite's major surface protein, circumsporozoite protein (CSP), is a multifunctional protein required for sporozoite development and likely mediates several steps of this journey. In this study, we show that CSP has two conformational states, an adhesive conformation in which the C-terminal cell-adhesive domain is exposed and a nonadhesive conformation in which the N terminus masks this domain. We demonstrate that the cell-adhesive domain functions in sporozoite development and hepatocyte invasion. Between these two events, the sporozoite must travel from the mosquito midgut to the mammalian liver, and N-terminal masking of the cell-adhesive domain maintains the sporozoite in a migratory state. In the mammalian host, proteolytic cleavage of CSP regulates the switch to an adhesive conformation, and the highly conserved region I plays a critical role in this process. If the CSP domain architecture is altered such that the cell-adhesive domain is constitutively exposed, the majority of sporozoites do not reach their target organs, and in the mammalian host, they initiate a blood stage infection directly from the inoculation site. These data provide structure-function information relevant to malaria vaccine development.

Insulin and insulin-like growth factor I receptors utilize different G protein signaling components.

We examined the role of heterotrimeric G protein signaling components in insulin and insulin-like growth factor I (IGF-I) action. In HIRcB cells and in 3T3L1 adipocytes, treatment with the Galpha(i) inhibitor (pertussis toxin) or microinjection of the Gbetagamma inhibitor (glutathione S-transferase-betaARK) inhibited IGF-I and lysophosphatidic acid-stimulated mitogenesis but had no effect on epidermal growth factor (EGF) or insulin action. In basal state, Galpha(i) and Gbeta were associated with the IGF-I receptor (IGF-IR), and after ligand stimulation the association of IGF-IR with Galpha(i) increased concomitantly with a decrease in Gbeta association. No association of Galpha(i) was found with either the insulin or EGF receptor. Microinjection of anti-beta-arrestin-1 antibody specifically inhibited IGF-I mitogenic action but had no effect on EGF or insulin action. beta-Arrestin-1 was associated with the receptors for IGF-I, insulin, and EGF in a ligand-dependent manner. We demonstrated that Galpha(i), betagamma subunits, and beta-arrestin-1 all play a critical role in IGF-I mitogenic signaling. In contrast, neither metabolic, such as GLUT4 translocation, nor mitogenic signaling by insulin is dependent on these protein components. These results suggest that insulin receptors and IGF-IRs can function as G protein-coupled receptors and engage different G protein partners for downstream signaling.

Primordial neurosecretory apparatus identified in the choanoflagellate Monosiga brevicollis.

SNARE protein-driven secretion of neurotransmitters from synaptic vesicles is at the center of neuronal communication. In the absence of the cytosolic protein Munc18-1, synaptic secretion comes to a halt. Although it is believed that Munc18-1 orchestrates SNARE complexes, its mode of action is still a matter of debate. In particular, it has been challenging to clarify the role of a tight Munc18/syntaxin 1 complex, because this interaction interferes strongly with syntaxin's ability to form a SNARE complex. In this complex, two regions of syntaxin, the N-peptide and the remainder in closed conformation, bind to Munc18 simultaneously. Until now, this binary complex has been reported for neuronal tissues only, leading to the hypothesis that it might be a specialization of the neuronal secretion apparatus. Here we aimed, by comparing the core secretion machinery of the unicellular choanoflagellate Monosiga brevicollis with that of animals, to reconstruct the ancestral function of the Munc18/syntaxin1 complex. We found that the Munc18/syntaxin 1 complex from M. brevicollis is structurally and functionally highly similar to the vertebrate complex, suggesting that it constitutes a fundamental step in the reaction pathway toward SNARE assembly. We thus propose that the primordial secretion machinery of the common ancestor of choanoflagellates and animals has been co-opted for synaptic roles during the rise of animals.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Calcineurin-Mediated Regulation of Hyphal Growth, Septation, and Virulence in Aspergillus fumigatus.

Calcineurin is a heterodimeric protein phosphatase complex composed of catalytic (CnaA) and regulatory (CnaB) subunits and plays diverse roles in regulating fungal stress responses, morphogenesis, and pathogenesis. Fungal pathogens utilize the calcineurin pathway to survive in the host environment and cause life-threatening infections. The immunosuppressive calcineurin inhibitors (FK506 and cyclosporine A) are active against fungi, making calcineurin a promising antifungal drug target. Here, we review novel findings on calcineurin localization and functions in Aspergillus fumigatus hyphal growth and septum formation through regulation of proteins involved in cell wall biosynthesis. Extensive mutational analysis in the functional domains of A. fumigatus CnaA has led to an understanding of the relevance of these domains for the localization and function of CnaA at the hyphal septum. An evolutionarily conserved novel mode of calcineurin regulation by phosphorylation in filamentous fungi was found to be responsible for virulence in A. fumigatus. This finding of a filamentous fungal-specific mechanism controlling hyphal growth and virulence represents a potential target for antifungal therapy.

Retinal pigment epithelium protein of 65 kDA gene-linked retinal degeneration is not modulated by chicken acidic leucine-rich epidermal growth factor-like domain containing brain protein/Neuroglycan C/ chondroitin sulfate proteoglycan 5.

PURPOSE: To analyze in vivo the function of chicken acidic leucine-rich epidermal growth factor-like domain containing brain protein/Neuroglycan C (gene symbol: Cspg5) during retinal degeneration in the Rpe65⁻/⁻ mouse model of Leber congenital amaurosis. METHODS: We resorted to mice with targeted deletions in the Cspg5 and retinal pigment epithelium protein of 65 kDa (Rpe65) genes (Cspg5⁻/⁻/Rpe65⁻/⁻). Cone degeneration was assessed with cone-specific peanut agglutinin staining. Transcriptional expression of rhodopsin (Rho), S-opsin (Opn1sw), M-opsin (Opn1mw), rod transducin α subunit (Gnat1), and cone transducin α subunit (Gnat2) genes was assessed with quantitative PCR from 2 weeks to 12 months. The retinal pigment epithelium (RPE) was analyzed at P14 with immunodetection of the retinol-binding protein membrane receptor Stra6. RESULTS: No differences in the progression of retinal degeneration were observed between the Rpe65⁻/⁻ and Cspg5⁻/⁻/Rpe65⁻/⁻ mice. No retinal phenotype was detected in the late postnatal and adult Cspg5⁻/⁻ mice, when compared to the wild-type mice. CONCLUSIONS: Despite the previously reported upregulation of Cspg5 during retinal degeneration in Rpe65⁻/⁻ mice, no protective effect or any involvement of Cspg5 in disease progression was identified.