Impact of T cell receptor affinity on the molecular mechanisms modulating CD8 T cell signalling and function against NY-ESO-1 tumour antigen

It is well established that cytotoxic T lymphocytes play a pivotal role in the protection against intracellular pathogens and tumour cells. Such protective immune responses rely on the specific T cell receptor (TCR)-mediated recognition by CD8 T cells of small antigenic peptides presented in the context of class-I Major Histocompatibility Complex molecules (pMHCs) on the surface of infected or malignant cells. The strength (affinity/avidity) of this interaction is a major correlate of protection. Although tumour-reactive CD8 T cells can be observed in cancer patients, anti-tumour immune responses are often ineffective in controlling or eradicating the disease due to the relative low TCR affinity of these cells. To overcome this limitation, tumour-specific CD8 T cells can be genetically modified to express TCRs of improved binding strength against a defined tumour antigen before adoptive cell transfer into cancer patients. We previously generated a panel of TCRs specific for the cancer-testis antigen NY-ESO-l,57.165 with progressively increased affinities for the pMHC complex, thus providing us with a unique tool to investigate the causal link between the surface expression of such TCRs and T cell activation and function. We recently demonstrated that anti-tumour CD8 T cell reactivity could only be improved within physiological affinity limits, beyond which drastic functional declines were observed, suggesting the presence of multiple regulatory mechanisms limiting T cell activation and function in a TCR affinity-dependent manner. The overarching goal of this thesis was (i) to assess the precise impact of TCR affinity on T cell activation and signalling at the molecular level and (ii) to gain further insights on the mechanisms that regulate and delimitate maximal/optimized CD8 T cell activation and signalling. Specifically, by combining several technical approaches we characterized the activation status of proximal (i.e. CD3Ç, Lek, and ZAP-70) and distal (i.e. ERK1/2) signalling molecules along the TCR affinity gradient. Moreover, we assessed the extent of TCR downmodulation, a critical step for initial T cell activation. CD8 T cells engineered with the optimal TCR affinity variants showed increased activation levels of both proximal and distal signalling molecules when compared to the wild-type T cells. Our analyses also highlighted the "paradoxical" status of tumour-reactive CD8 T cells bearing very high TCR affinities, which retained strong proximal signalling capacity and TCR downmodulation, but were unable to propagate signalling distally (i.e. pERKl/2), resulting in impaired cell-mediated functions. Importantly, these very high affinity T cells displayed maximal levels of SHP-1 and SHP-2 phosphatases, two negative regulatory molecules, and this correlated with a partial pERKl/2 signalling recovery upon pharmacological SHP-l/SHP-2 inhibition. These findings revealed the putative presence of inhibitory regulators of the TCR signalling cascade acting very rapidly following tumour-specific stimulation. Moreover, the very high affinity T cells were only able to transiently express enhanced proximal signalling molecules, suggesting the presence of an additional level of regulation that operates through the activation of negative feedback loops over time, limiting the duration of the TCR-mediated signalling. Overall, the determination of TCR-pMHC binding parameters eliciting optimal CD8 T cell activation, signalling, and effector function while guaranteeing high antigen specificity, together with the identification of critical regulatory mechanisms acting proximally in the TCR signalling cascade, will directly contribute to optimize and support the development of future TCR-based adoptive T cell strategies for the treatment of malignant diseases. -- Les lymphocytes T CD8 cytotoxiques jouent un rôle prédominant dans la protection contre les pathogènes intracellulaires et les cellules tumorales. Ces réponses immunitaires dépendent de la spécificité avec laquelle les récepteurs T (TCR) des lymphocytes CD8 reconnaissent les peptides antigéniques présentés par les molécules du complexe Majeur de Histocompatibilité de classe I (pCMH) à la surface des cellules infectées ou malignes. La force (ou affinité/avidité) de l'interaction du TCR-pCMH est un corrélat majeur de protection. Les réponses immunitaires sont cependant souvent inefficaces et ne permettent pas de contrôler ou d'éliminer les cellules tumorales chez les patients atteint du cancer, et ce à cause de la relative faible reconnaissance des TCRs exprimés par les lymphocytes T CD8 envers les antigènes tumoraux. Afin de surmonter cette limitation, les cellules T anti-tumorales peuvent être génétiquement modifiées en les dotant de TCRs préalablement optimisés afin d'augmenter leur reconnaissance ou affinité contre les antigènes tumoraux, avant leur ré¬infusion dans le patient. Nous avons récemment généré des cellules T CD8 exprimant un panel de TCRs spécifiques pour l'antigène tumoral NY-ESO-l157.16J avec des affinités croissantes, permettant ainsi d'investiguer la causalité directe entre l'affinité du TCR-pCMH et la fonction des cellules T CD8. Nous avons démontré que la réactivité anti-tumorale pouvait être améliorée en augmentant l'affinité du TCR dans une intervalle physiologique, mais au delà duquel nous observons un important déclin fonctionnel. Ces résultats suggèrent la présence de mécanismes de régulation limitant l'activation des cellules T de manière dépendante de l'affinité du TCR. Le but de cette thèse a été (i) de définir l'impact précis de l'affinité du TCR sur l'activation et la signalisation des cellules T CD8 au niveau moléculaire et (ii) d'acquérir de nouvelles connaissances sur les mécanismes qui régulent et délimitent l'activation et la signalisation maximale des cellules T CD8 optimisées. Spécifiquement, en combinant plusieurs approches technologiques, nous avons caractérisé l'état d'activation de différentes protéines de la voie de signalisation proximale (CD3Ç, Lek et ZAP-70) et distale (ERK1/2) le long du gradient d'affinité du TCR, ainsi que l'internalisation du TCR, une étape clef dans l'activation initiale des cellules T. Les lymphocytes T CD8 exprimant des TCRs d'affinité optimale ont montré des niveaux d'activation augmentés des molécules proximales et distales par rapport aux cellules de type sauvage (wild-type). Nos analyses ont également mis en évidence un paradoxe chez les cellules T CD8 équipées avec des TCRs de très haute affinité. En effet, ces cellules anti-tumorales sont capables d'activer leurs circuits biochimiques au niveau proximal et d'internaliser efficacement leur TCR, mais ne parviennent pas à propager les signaux biochimiques dépendants du TCR jusqu'au niveau distal (via phospho-ERKl/2), avec pour conséquence une limitation de leur capacité fonctionnelle. Finalement, nous avons démontré que SHP-1 et SHP-2, deux phosphatases avec des propriétés régulatrices négatives, étaient majoritairement exprimées dans les cellules T CD8 de très hautes affinités. Une récupération partielle des niveaux d'activation de ERK1/2 a pu être observée après l'inhibition pharmacologique de ces phosphatases. Ces découvertes révèlent la présence de régulateurs moléculaires qui inhibent le complexe de signalisation du TCR très rapidement après la stimulation anti-tumorale. De plus, les cellules T de très hautes affinités ne sont capables d'activer les molécules de la cascade de signalisation proximale que de manière transitoire, suggérant ainsi un second niveau de régulation via l'activation de mécanismes de rétroaction prenant place progressivement au cours du temps et limitant la durée de la signalisation dépendante du TCR. En résumé, la détermination des paramètres impliqués dans l'interaction du TCR-pCMH permettant l'activation de voies de signalisation et des fonctions effectrices optimales ainsi que l'identification des mécanismes de régulation au niveau proximal de la cascade de signalisation du TCR contribuent directement à l'optimisation et au développement de stratégies anti-tumorales basées sur l'ingénierie des TCRs pour le traitement des maladies malignes.

Regulation of B Cell Gene Expression and Function by Ikaros, Helios and Bcl6

B lymphocytes constitute a key branch of adaptive immunity by providing specificity to recognize a vast variety of antigens by B cell antigen receptors (BCR) and secreted antibodies. Antigen recognition activates the cells and can produce antibody secreting plasma cells via germinal center reaction that leads to the maturation of antigen recognition affinity and switching of antibody effector class. The specificity of antigen recognition is achieved through a multistep developmental pathway that is organized by interplay of transcription factors and signals through BCR. Lymphoid malignancies arise from different stages of development in abnormal function of transcriptional regulation. To understand the B cell development and the function of B cells, a thorough understanding of the regulation of gene expression is important. The transcription factors of the Ikaros family and Bcl6 are frequently associated with lymphoma generation. The aim of this study was to reveal the targets of Ikaros, Helios and Bcl6 mediated gene regulation and to find out the function of Ikaros and Helios in B cells. This study uses gene targeted DT40 B cell lines and establishes a role for Ikaros family factors Ikaros and Helios in the regulation of BCR signaling that is important at developmental checkpoints, for cell survival and in activation. Ikaros and Helios had opposing roles in the regulation of BCR signals. Ikaros was found to directly repress the SHIP gene that encodes a signaling lipid-metabolizing enzyme, whereas Helios had activating effect on SHIP expression. The findings demonstrate a balancing function for these two Ikaros family transcription factors in the regulation of BCR signaling as well as in the regulation of gene expression. Bcl6 was found to repress plasma cell gene expression program while maintaining gene expression profile of B cells. Analysis of direct Bcl6 target genes suggested novel mechanisms for Bcl6-mediated suppression of plasma cell differentiation and promoting germinal center phenotype.

P-glycoprotein-mediated resistance to chemotherapy in cancer cells: using recombinant cytosolic domains to establish structure-function relationships

Resistance to chemotherapy in cancer cells is mainly mediated by overexpression of P-glycoprotein (Pgp), a plasma membrane ATP-binding cassette (ABC) transporter which extrudes cytotoxic drugs at the expense of ATP hydrolysis. Pgp consists of two homologous halves each containing a transmembrane domain and a cytosolic nucleotide-binding domain (NBD) which contains two consensus Walker motifs, A and B, involved in ATP binding and hydrolysis. The protein also contains an S signature characteristic of ABC transporters. The molecular mechanism of Pgp-mediated drug transport is not known. Since the transporter has an extraordinarily broad substrate specificity, its cellular function has been described as a "hydrophobic vacuum cleaner". The limited knowledge about the mechanism of Pgp, partly due to the lack of a high-resolution structure, is well reflected in the failure to efficiently inhibit its activity in cancer cells and thus to reverse multidrug resistance (MDR). In contrast to the difficulties encountered when studying the full-length Pgp, the recombinant NBDs can be obtained in large amounts as soluble proteins. The biochemical and biophysical characterization of recombinant NBDs is shown here to provide a suitable alternative route to establish structure-function relationships. NBDs were shown to bind ATP and analogues as well as potent modulators of MDR, such as hydrophobic steroids, at a region close to the ATP site. Interestingly, flavonoids also bind to NBDs with high affinity. Their binding site partly overlaps both the ATP-binding site and the steroid-interacting region. Therefore flavonoids constitute a new promising class of bifunctional modulators of Pgp.

Insights into the physiological function of cellular prion protein

Prions have been extensively studied since they represent a new class of infectious agents in which a protein, PrPsc (prion scrapie), appears to be the sole component of the infectious particle. They are responsible for transmissible spongiform encephalopathies, which affect both humans and animals. The mechanism of disease propagation is well understood and involves the interaction of PrPsc with its cellular isoform (PrPc) and subsequently abnormal structural conversion of the latter. PrPc is a glycoprotein anchored on the cell surface by a glycosylphosphatidylinositol moiety and expressed in most cell types but mainly in neurons. Prion diseases have been associated with the accumulation of the abnormally folded protein and its neurotoxic effects; however, it is not known if PrPc loss of function is an important component. New efforts are addressing this question and trying to characterize the physiological function of PrPc. At least four different mouse strains in which the PrP gene was ablated were generated and the results regarding their phenotype are controversial. Localization of PrPc on the cell membrane makes it a potential candidate for a ligand uptake, cell adhesion and recognition molecule or a membrane signaling molecule. Recent data have shown a potential role for PrPc in the metabolism of copper and moreover that this metal stimulates PrPc endocytosis. Our group has recently demonstrated that PrPc is a high affinity laminin ligand and that this interaction mediates neuronal cell adhesion and neurite extension and maintenance. Moreover, PrPc-caveolin-1 dependent coupling seems to trigger the tyrosine kinase Fyn activation. These data provide the first evidence for PrPc involvement in signal transduction.

Dimensions and dynamics in integrin function

Integrins play crucial roles in cell adhesion, migration, and signaling by providing transmembrane links between the extracellular matrix and the cytoskeleton. Integrins cluster in macromolecular complexes to generate cell-matrix adhesions such as focal adhesions. In this mini-review, we compare certain integrin-based biological responses and signaling during cell interactions with standard 2D cell culture versus 3D matrices. Besides responding to the composition of the matrix, cells sense and react to physical properties that include three-dimensionality and rigidity. In routine cell culture, fibroblasts and mesenchymal cells appear to use focal adhesions as anchors. They then use intracellular actomyosin contractility and dynamic, directional integrin movements to stretch cell-surface fibronectin and to generate characteristic long fibrils of fibronectin in "fibrillar adhesions". Some cells in culture proceed to produce dense, three-dimensional matrices similar to in vivo matrix, as opposed to the flat, rigid, two-dimensional surfaces habitually used for cell culture. Cells within such more natural 3D matrices form a distinctive class of adhesion termed "3D-matrix adhesions". These 3D adhesions show distinctive morphology and molecular composition. Their formation is heavily dependent on interactions between integrin alpha5ß1 and fibronectin. Cells adhere much more rapidly to 3D matrices. They also show more rapid morphological changes, migration, and proliferation compared to most 2D matrices or 3D collagen gels. Particularly notable are low levels of tyrosine phosphorylation of focal adhesion kinase and moderate increases in activated mitogen-activated protein kinase. These findings underscore the importance of the dimensionality and dynamics of matrix substrates in cellular responses to the extracellular matrix.

Modulation of B lymphocyte function by an aqueous fraction of the ethanol extract of Cissampelos sympodialis Eichl (Menispermaceae)

Cissampelos sympodialis Eichl species are used in folk medicine for the treatment of asthma, arthritis and rheumatism. In the present study, we investigated the immunomodulatory effect of an aqueous fraction of a 70% (v/v) ethanol extract of C. sympodialis leaves on B lymphocyte function. The hydroalcoholic extract inhibited the in vitro proliferative response of resting B cells induced by LPS (IC50 = 17.2 µg/ml), anti-delta-dextran (IC50 = 13.9 µg/ml) and anti-IgM (IC50 = 24.3 µg/ml) but did not affect the anti-MHC class II antibody-stimulated proliferative response of B cell blasts obtained by stimulation with IL-4 and anti-IgM. Incubation with the hydroalcoholic extract used at 50 µg/ml induced a 700% increase in intracellular cAMP levels. IgM secretion by resting B cells (obtained from normal mice) and polyclonally activated B cells (obtained from Trypanosoma cruzi-infected animals) was inhibited by the hydroalcoholic extract. The latter were more sensitive to the hydroalcoholic extract since 6.5 µg/ml induced a 20% inhibition in the response of cells from normal mice while it inhibited the response of B cells from infected animals by 75%. The present data indicate that the alcoholic extract of C. sympodialis inhibited B cell function through an increase in intracellular cAMP levels. The finding that the hydroalcoholic extract inhibited immunoglobulin secretion suggests a therapeutic use for the extract from C. sympodialis in conditions associated with unregulated B cell function and enhanced immunoglobulin secretion. Finally, the inhibitory effect of the hydroalcoholic extract on B cells may indicate an anti-inflammatory effect of this extract.

Diastolic function is associated with quality of life and exercise capacity in stable heart failure patients with reduced ejection fraction

Exercise capacity and quality of life (QOL) are important outcome predictors in patients with systolic heart failure (HF), independent of left ventricular (LV) ejection fraction (LVEF). LV diastolic function has been shown to be a better predictor of aerobic exercise capacity in patients with systolic dysfunction and a New York Heart Association (NYHA) classification ≥II. We hypothesized that the currently used index of diastolic function E/e' is associated with exercise capacity and QOL, even in optimally treated HF patients with reduced LVEF. This prospective study included 44 consecutive patients aged 55±11 years (27 men and 17 women), with LVEF<0.50 and NYHA functional class I-III, receiving optimal pharmacological treatment and in a stable clinical condition, as shown by the absence of dyspnea exacerbation for at least 3 months. All patients had conventional transthoracic echocardiography and answered the Minnesota Living with HF Questionnaire, followed by the 6-min walk test (6MWT). In a multivariable model with 6MWT as the dependent variable, age and E/e' explained 27% of the walked distance in 6MWT (P=0.002; multivariate regression analysis). No association was found between walk distance and LVEF or mitral annulus systolic velocity. Only normalized left atrium volume, a sensitive index of diastolic function, was associated with decreased QOL. Despite the small number of patients included, this study offers evidence that diastolic function is associated with physical capacity and QOL and should be considered along with ejection fraction in patients with compensated systolic HF.

Novel glutathione disulfide transferase function of CC-glutaredoxins involved in disease resistance and flower development

Glutaredoxins are oxidoreductases capable of reducing protein disulfide bridges and glutathione mixed disulfides through the process of deglutathionylation and glutathionylation. Lately, redox-mediated modifications of functional cysteine residues of TGA1 and TGA8 transcription factors have been postulated. Namely, GRX480 and ROXY1 glutaredoxins have been previously shown to interact with TGA proteins and have been suggested to regulate redox state of these proteins. TGA1, together with TGA2, is involved in systemic acquired resistance (SAR) establishment in the plant Arabidopsis thaliana through PR1 (Pathogenesis related 1) gene activation. They both form an enhanceosome complex with the NPR1 protein (non-expressor of pathogenesis related gene 1) which leads to PR1 transcription. Although TGA1 is capable of activating PR1 transcription, the ability of the TGA1 NPR1 enhanceosome complex to assembly is based on the redox status of TGA1. We identified GRX480 as a glutathionylating enzyme that catalyzes the TGA1 glutathione disulfide transferase reaction with a Km of around 20μM GSSG (oxidized glutathione). Out of four cysteine residues found within TGA1, C172 and C266 were found to be glutathionylated by this enzyme. We also confirmed TGA1 glutathionylation in vivo and showed that this modification takes place while TGA1 is associated with the PR1 promoter enzymatically via GRX480. Furthermore, we show that glutathionylation via GRX480 abolishes TGA1's interaction with NPR1 and consequently prevents the TGA1-NPR1 transcription activation of PR1. When glutathionylated, TGA1 is recruited to the PR1 promoter and acts as a repressor. Therefore, glutathionylation is a mechanism that prevents TGA1 NPR1 interaction, allowing TGA1 to function as a repressor of PR1 transcription. Surprisingly, GRX480 was not able to deglutathionylate proteins demonstrating the irreversible nature of the reaction. Moreover, we demonstrate that other members of CC-class glutaredoxins, namely ROXY1 and ROXY2, can also catalyze protein glutathionylation. The TGA8 protein was previously shown to interact with NPR1 analogs, BOP1 and BOP2 proteins. However, unlike the case of TGA1 NPR1 interaction, here we demonstrate that TGA8-BOP1 interaction is not redox regulated and that TGA8 glutathionylation by ROXY1 and ROXY2 enzymes does not abolish this interaction in vitro. However, TGA8 glutathionylation results in TGA8 oligomer disassembly into smaller complexes and monomers. Our results suggest that CC-Grxs are unable to reduce mixed disulfides, instead they efficiently catalyze the opposite reaction which distinguishes them from traditional glutaredoxins. Therefore, they should not be classified as glutaredoxins but as protein glutathione disulfide transferases.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Measure Fields for Function Approximation

The computation of a piecewise smooth function that approximates a finite set of data points may be decomposed into two decoupled tasks: first, the computation of the locally smooth models, and hence, the segmentation of the data into classes that consist on the sets of points best approximated by each model, and second, the computation of the normalized discriminant functions for each induced class. The approximating function may then be computed as the optimal estimator with respect to this measure field. We give an efficient procedure for effecting both computations, and for the determination of the optimal number of components.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

Are class II phosphoinositide 3-kinases potential targets for anticancer therapies?

Of the three classes of true phosphoinositide (PI) 3-kinases, the class II subdivision, which consists of three isoforms, PI3K-C2alpha, PI3K-C2beta and PI3K-C2gamma, is the least well understood. There are a number of reasons for this. This class of PI 3-kinase was identified exclusively by PCR and homology cloning approaches and not on the basis of cellular function. Like class I PI 3-kinases, class II PI 3-kinases are activated by diverse receptor types. To complicate the elucidation of class II PI 3-kinase function further, their in vitro substrate specificity is intermediate between the receptor activated class I PI 3-kinases and the housekeeping class III PI 3-kinase. The class II PI 3-kinases are inhibited by the two commonly used PI 3-kinase family selective inhibitors, wortmannin and LY294002, and there are no widely available, specific inhibitors for the individual classes or isoforms. Here the current state of understanding of class II PI 3-kinase function is reviewed, followed by an appraisal as to whether there is enough evidence to suggest that pharmaceutical companies, who are currently targeting the class I PI 3-kinases in an attempt to generate anticancer agents, should also consider targeting the class II PI 3-kinases.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

Grey-box radial basis function modelling: the art of incorporating prior knowledge

A basic principle in data modelling is to incorporate available a priori information regarding the underlying data generating mechanism into the modelling process. We adopt this principle and consider grey-box radial basis function (RBF) modelling capable of incorporating prior knowledge. Specifically, we show how to explicitly incorporate the two types of prior knowledge: the underlying data generating mechanism exhibits known symmetric property and the underlying process obeys a set of given boundary value constraints. The class of orthogonal least squares regression algorithms can readily be applied to construct parsimonious grey-box RBF models with enhanced generalisation capability.

Fully complex-valued radial basis function networks: orthogonal least squares regression and classification

We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF models, is extended to the fully complex-valued RBF (CVRBF) network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully CVRBF network. The proposed fully CVRBF network is also applied to four-class classification problems that are typically encountered in communication systems. A complex-valued orthogonal forward selection algorithm based on the multi-class Fisher ratio of class separability measure is derived for constructing sparse CVRBF classifiers that generalise well. The effectiveness of the proposed algorithm is demonstrated using the example of nonlinear beamforming for multiple-antenna aided communication systems that employ complex-valued quadrature phase shift keying modulation scheme. (C) 2007 Elsevier B.V. All rights reserved.