Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

Drugs down-regulating E2F-1 expression hinders cell proliferation through a p53-indipendent mechanism

E2F-1 is a transcription factor that plays a key role in cell-cycle control at G1/S check-point level by regulating the timely expression of many target genes whose products are required for S phase entry and progression. In mammalian cells, E2F-1 is negatively regulated by hypo-phosphorylated Retinoblastoma protein (pRb) whereas it is protected against degradation by its binding to Mouse Double Minute 2 protein (MDM2). In this study we experimented a drug combination in order to obtain a strong down-regulation of E2F-1 by acting on two different mechanisms of E2F-1 regulation mentioned above. This was achieved by combining drugs inhibiting the phosphorylation of pRb with drugs inactivating the MDM2 binding capability. The mechanism of action of these drugs in down-regulating E2F-1 level and activity is p53 independent. As expected, when combined, these drugs strongly inhibits E2F-1 and hinder cell proliferation in p53-/- and p53-mutated cells by blocking them in G1 phase of cell cycle, suggesting that E2F-1 down-regulation may represent a valid chemotherapeutic approach to inhibit proliferation in tumors independently of p53 status.

Computational analyses on the structure-function relation in ion channels

Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

Bioimaging of animal embryogenesis: mathematical methods and computational algorithms

Some fundamental biological processes such as embryonic development have been preserved during evolution and are common to species belonging to different phylogenetic positions, but are nowadays largely unknown. The understanding of cell morphodynamics leading to the formation of organized spatial distribution of cells such as tissues and organs can be achieved through the reconstruction of cells shape and position during the development of a live animal embryo. We design in this work a chain of image processing methods to automatically segment and track cells nuclei and membranes during the development of a zebrafish embryo, which has been largely validates as model organism to understand vertebrate development, gene function and healingrepair mechanisms in vertebrates. The embryo is previously labeled through the ubiquitous expression of fluorescent proteins addressed to cells nuclei and membranes, and temporal sequences of volumetric images are acquired with laser scanning microscopy. Cells position is detected by processing nuclei images either through the generalized form of the Hough transform or identifying nuclei position with local maxima after a smoothing preprocessing step. Membranes and nuclei shapes are reconstructed by using PDEs based variational techniques such as the Subjective Surfaces and the Chan Vese method. Cells tracking is performed by combining informations previously detected on cells shape and position with biological regularization constraints. Our results are manually validated and reconstruct the formation of zebrafish brain at 7-8 somite stage with all the cells tracked starting from late sphere stage with less than 2% error for at least 6 hours. Our reconstruction opens the way to a systematic investigation of cellular behaviors, of clonal origin and clonal complexity of brain organs, as well as the contribution of cell proliferation modes and cell movements to the formation of local patterns and morphogenetic fields.

Development of synthetic molecular circuits for the control of cell systems

Synthetic biology is a young field of applicative research aiming to design and build up artificial biological devices, useful for human applications. How synthetic biology emerged in past years and how the development of the Registry of Standard Biological Parts aimed to introduce one practical starting solution to apply the basics of engineering to molecular biology is presented in chapter 1 in the thesis The same chapter recalls how biological parts can make up a genetic program, the molecular cloning tecnique useful for this purpose, and an overview of the mathematical modeling adopted to describe gene circuit behavior. Although the design of gene circuits has become feasible the increasing complexity of gene networks asks for a rational approach to design gene circuits. A bottom-up approach was proposed, suggesting that the behavior of a complicated system can be predicted from the features of its parts. The option to use modular parts in large-scale networks will be facilitated by a detailed and shared characterization of their functional properties. Such a prediction, requires well-characterized mathematical models of the parts and of how they behave when assembled together. In chapter 2, the feasibility of the bottom-up approach in the design of a synthetic program in Escherichia coli bacterial cells is described. The rational design of gene networks is however far from being established. The synthetic biology approach can used the mathematical formalism to identify biological information not assessable with experimental measurements. In this context, chapter 3 describes the design of a synthetic sensor for identifying molecules of interest inside eukaryotic cells. The Registry of Standard parts collects standard and modular biological parts. To spread the use of BioBricks the iGEM competition was started. The ICM Laboratory, where Francesca Ceroni completed her Ph.D, partecipated with teams of students and Chapter 4 summarizes the projects developed.

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Computational Modelling of Cardiac Electrophysiology: from Cell to Bedside

Heart diseases are the leading cause of death worldwide, both for men and women. However, the ionic mechanisms underlying many cardiac arrhythmias and genetic disorders are not completely understood, thus leading to a limited efficacy of the current available therapies and leaving many open questions for cardiac electrophysiologists. On the other hand, experimental data availability is still a great issue in this field: most of the experiments are performed in vitro and/or using animal models (e.g. rabbit, dog and mouse), even when the final aim is to better understand the electrical behaviour of in vivo human heart either in physiological or pathological conditions. Computational modelling constitutes a primary tool in cardiac electrophysiology: in silico simulations, based on the available experimental data, may help to understand the electrical properties of the heart and the ionic mechanisms underlying a specific phenomenon. Once validated, mathematical models can be used for making predictions and testing hypotheses, thus suggesting potential therapeutic targets. This PhD thesis aims to apply computational cardiac modelling of human single cell action potential (AP) to three clinical scenarios, in order to gain new insights into the ionic mechanisms involved in the electrophysiological changes observed in vitro and/or in vivo. The first context is blood electrolyte variations, which may occur in patients due to different pathologies and/or therapies. In particular, we focused on extracellular Ca2+ and its effect on the AP duration (APD). The second context is haemodialysis (HD) therapy: in addition to blood electrolyte variations, patients undergo a lot of other different changes during HD, e.g. heart rate, cell volume, pH, and sympatho-vagal balance. The third context is human hypertrophic cardiomyopathy (HCM), a genetic disorder characterised by an increased arrhythmic risk, and still lacking a specific pharmacological treatment.

Study of apoptotic deletion mediated by Bifidobacterium longum with construction of recombinant strains for Serpin encoding gene and phenotypes comparison in a pig cell model

The first part of the research project of the Co-Advisorship Ph.D Thesis was aimed to select the best Bifidobacterium longum strains suitable to set the basis of our study. We were looking for strains with the abilities to colonize the intestinal mucosa and with good adhesion capacities, so that we can test these strains to investigate their ability to induce apoptosis in “damaged” intestinal cells. Adhesion and apoptosis are the two process that we want to study to better understand the role of an adhesion protein that we have previously identified and that have top scores homologies with the recent serpin encoding gene identified in B. longum by Nestlè researchers. Bifidobacterium longum is a probiotic, known for its beneficial effects to the human gut and even for its immunomodulatory and antitumor activities. Recently, many studies have stressed out the intimate relation between probiotic bacteria and the GIT mucosa and their influence on human cellular homeostasis. We focused on the apoptotic deletion of cancer cells induced by B. longum. This has been valued in vitro, performing the incubation of three B.longum strains with enterocyte-like Caco- 2 cells, to evidence DNA fragmentation, a cornerstone of apoptosis. The three strains tested were defined for their adhesion properties using adhesion and autoaggregation assays. These features are considered necessary to select a probiotic strain. The three strains named B12, B18 and B2990 resulted respectively: “strong adherent”, “adherent” and “non adherent”. Then, bacteria were incubated with Caco-2 cells to investigate apoptotic deletion. Cocultures of Caco-2 cells with B. longum resulted positive in DNA fragmentation test, only when adherent strains were used (B12 and B18). These results indicate that the interaction with adherent B. longum can induce apoptotic deletion of Caco-2 cells, suggesting a role in cellular homeostasis of the gastrointestinal tract and in restoring the ecology of damaged colon tissues. These results were used to keep on researching and the strains tested were used as recipient of recombinant techniques aimed to originate new B.longum strains with enhanced capacity of apoptotic induction in “damaged” intestinal cells. To achieve this new goal it was decided to clone the serpin encoding gene of B. longum, so that we can understand its role in adhesion and apoptosis induction. Bifidobacterium longum has immunostimulant activity that in vitro can lead to apoptotic response of Caco-2 cell line. It secretes a hypothetical eukaryotic type serpin protein, which could be involved in this kind of deletion of damaged cells. We had previously characterised a protein that has homologies with the hypothetical serpin of B. longum (DD087853). In order to create Bifidobacterium serpin transformants, a B. longum cosmid library was screened with a PCR protocol using specific primers for serpin gene. After fragment extraction, the insert named S1 was sub-cloned into pRM2, an Escherichia coli - Bifidobacterium shuttle vector, to construct pRM3. Several protocols for B. longum transformation were performed and the best efficiency was obtained using MRS medium and raffinose. Finally bacterial cell supernatants were tested in a dotblot assay to detect antigens presence against anti-antitrypsin polyclonal antibody. The best signal was produced by one starin that has been renamed B. longum BLKS 7. Our research study was aimed to generate transformants able to over express serpin encoding gene, so that we can have the tools for a further study on bacterial apoptotic induction of Caco-2 cell line. After that we have originated new trasformants the next step to do was to test transformants abilities when exposed to an intestinal cell model. In fact, this part of the project was achieved in the Department of Biochemistry of the Medical Faculty of the University of Maribor, guest of the abroad supervisor of the Co-Advisorship Doctoral Thesis: Prof. Avrelija Cencic. In this study we examined the probiotic ability of some bacterial strains using intestinal cells from a 6 years old pig. The use of intestinal mammalian cells is essential to study this symbiosis and a functional cell model mimics a polarised epithelium in which enterocytes are separated by tight junctions. In this list of strains we have included the Bifidobacterium longum BKS7 transformant strain that we have previously originated; in order to compare its abilities. B. longum B12 wild type and B. longum BKS7 transformant and eight Lactobacillus strains of different sources were co-cultured with porcine small intestine epithelial cells (PSI C1) and porcine blood monocytes (PoM2) in Transwell filter inserts. The strains, including Lb. gasseri, Lb. fermentum, Lb. reuterii, Lb. plantarum and unidentified Lactobacillus from kenyan maasai milk and tanzanian coffee, were assayed for activation of cell lines, measuring nitric oxide by Griess reaction, H202 by tetramethylbenzidine reaction and O2 - by cytochrome C reduction. Cytotoxic effect by crystal violet staining and induction on metabolic activity by MTT cell proliferation assay were tested too. Transepithelial electrical resistance (TER) of polarised PSI C1 was measured during 48 hours co-culture. TER, used to observe epithelium permeability, decrease during pathogenesis and tissue becomes permeable to ion passive flow lowering epithelial barrier function. Probiotics can prevent or restore increased permeability. Lastly, dot-blot was achieved against Interleukin-6 of treated cells supernatants. The metabolic activity of PoM2 and PSI C1 increased slightly after co-culture not affecting mitochondrial functions. No strain was cytotoxic over PSI C1 and PoM2 and no cell activation was observed, as measured by the release of NO2, H202 and O2 - by PoM2 and PSI C1. During coculture TER of polarised PSI C1 was two-fold higher comparing with constant TER (~3000 ) of untreated cells. TER raise generated by bacteria maintains a low permeability of the epithelium. During treatment Interleukin-6 was detected in cell supernatants at several time points, confirming immunostimulant activity. All results were obtained using Lactobacillus paracasei Shirota e Carnobacterium divergens as controls. In conclusion we can state that both the list of putative probiotic bacteria and our new transformant strain of B. longum are not harmful when exposed to intestinal cells and could be selected as probiotics, because can strengthen epithelial barrier function and stimulate nonspecific immunity of intestinal cells on a pig cell model. Indeed, we have found out that none of the strains tested that have good adhesion abilities presents citotoxicity to the intestinal cells and that non of the strains tested can induce cell lines to produce high level of ROS, neither NO2. Moreover we have assayed even the capacity of producing certain citokynes that are correlated with immune response. The detection of Interleukin-6 was assayed in all our samples, including B.longum transformant BKS 7 strain, this result indicates that these bacteria can induce a non specific immune response in the intestinal cells. In fact, when we assayed the presence of Interferon-gamma in cells supernatant after bacterial exposure, we have no positive signals, that means that there is no activation of a specific immune response, thus confirming that these bacteria are not recognize as pathogen by the intestinal cells and are certainly not harmful for intestinal cells. The most important result is the measure of Trans Epithelial Electric Resistance that have shown how the intestinal barrier function get strengthen when cells are exposed to bacteria, due to a reduction of the epithelium permeability. We have now a new strain of B. longum that will be used for further studies above the mechanism of apoptotic induction to “damaged cells” and above the process of “restoring ecology”. This strain will be the basis to originate new transformant strains for Serpin encoding gene that must have better performance and shall be used one day even in clinical cases as in “gene therapy” for cancer treatment and prevention.

Anticancer drug screening from images of zebrafish embryogenesis

During the previous 10 years, global R&D expenditure in the pharmaceuticals and biotechnology sector has steadily increased, without a corresponding increase in output of new medicines. To address this situation, the biopharmaceutical industry's greatest need is to predict the failures at the earliest possible stage of the drug development process. A major key to reducing failures in drug screenings is the development and use of preclinical models that are more predictive of efficacy and safety in clinical trials. Further, relevant animal models are needed to allow a wider testing of novel hypotheses. Key to this is the developing, refining, and validating of complex animal models that directly link therapeutic targets to the phenotype of disease, allowing earlier prediction of human response to medicines and identification of safety biomarkers. Morehover, well-designed animal studies are essential to bridge the gap between test in cell cultures and people. Zebrafish is emerging, complementary to other models, as a powerful system for cancer studies and drugs discovery. We aim to investigate this research area designing a new preclinical cancer model based on the in vivo imaging of zebrafish embryogenesis. Technological advances in imaging have made it feasible to acquire nondestructive in vivo images of fluorescently labeled structures, such as cell nuclei and membranes, throughout early Zebrafishsh embryogenesis. This In vivo image-based investigation provides measurements for a large number of features at cellular level and events including nuclei movements, cells counting, and mitosis detection, thereby enabling the estimation of more significant parameters such as proliferation rate, highly relevant for investigating anticancer drug effects. In this work, we designed a standardized procedure for accessing drug activity at the cellular level in live zebrafish embryos. The procedure includes methodologies and tools that combine imaging and fully automated measurements of embryonic cell proliferation rate. We achieved proliferation rate estimation through the automatic classification and density measurement of epithelial enveloping layer and deep layer cells. Automatic embryonic cells classification provides the bases to measure the variability of relevant parameters, such as cell density, in different classes of cells and is finalized to the estimation of efficacy and selectivity of anticancer drugs. Through these methodologies we were able to evaluate and to measure in vivo the therapeutic potential and overall toxicity of Dbait and Irinotecan anticancer molecules. Results achieved on these anticancer molecules are presented and discussed; furthermore, extensive accuracy measurements are provided to investigate the robustness of the proposed procedure. Altogether, these observations indicate that zebrafish embryo can be a useful and cost-effective alternative to some mammalian models for the preclinical test of anticancer drugs and it might also provides, in the near future, opportunities to accelerate the process of drug discovery.

Role of caveolin-1 in the proliferation of solid tumours in vitro

Caveolin-1 (Cav-1), the essential structural constituent of caveolae, which are flask-shaped invaginations of the plasma membrane, has been found to play a key role in the modulation of cell proliferation and cancer development. It seems to act as an oncosuppressor or a promoter of growth, depending on the histotype, stage and grade of each tumour. The aim of this study was to analyze the effects of Caveolin-1 gene silencing on the proliferation of human lung cancer and osteosarcoma in vitro. Our data show that Cav-1 silencing blocks the growth in both metastatic lung cancer cell lines analyzed, suggesting a proliferation promoting action of the protein in these cells. A marked decrease of phospho-Akt, phospho-ERK, STAT3, cyclin D1, CDK4 and consequently of phospho-Rb expression was evident in the cells treated with Cav-1 siRNA. With regards to osteosarcoma, we demonstrated that the suppression of Cav-1 results in the blocking of MG-63 and in the slowing down of HOS proliferation, suggesting a role for Cav-1 as a promoter of tumour growth in these cell lines. A marked decrease of phospho-Akt, cyclin E, CDK2 and phospho-Rb and an increase of p21 expression levels were evident in the cells treated with Cav-1 siRNA. Our results suggest two new cell cycle inhibiting pathways, mediated by Cav-1 knock-down, and provide new insights into the molecular mechanisms underlying the tumour-promoting role of Cav-1 in lung cancer and osteosarcoma. In this work we also investigated the role of estrogens in lung cancer and the functional cross-talk between Cav-1 and estrogens/estrogen receptors in it. Our results show that 17β-estradiol induces proliferation either in RAL or in SCLC-R1 cells and that both cell lines are sensitive to 4-OHT antiproliferative effect. The sensitivity to estrogen stimulation seems to be gender- and/or histological type-independent in metastatic lung cancer in vitro.

Models for the Study of Cortical Activity During Cognitive ans Motor Tasks

This thesis is mainly devoted to show how EEG data and related phenomena can be reproduced and analyzed using mathematical models of neural masses (NMM). The aim is to describe some of these phenomena, to show in which ways the design of the models architecture is influenced by such phenomena, point out the difficulties of tuning the dozens of parameters of the models in order to reproduce the activity recorded with EEG systems during different kinds of experiments, and suggest some strategies to cope with these problems. In particular the chapters are organized as follows: chapter I gives a brief overview of the aims and issues addressed in the thesis; in chapter II the main characteristics of the cortical column, of the EEG signal and of the neural mass models will be presented, in order to show the relationships that hold between these entities; chapter III describes a study in which a NMM from the literature has been used to assess brain connectivity changes in tetraplegic patients; in chapter IV a modified version of the NMM is presented, which has been developed to overcomes some of the previous version’s intrinsic limitations; chapter V describes a study in which the new NMM has been used to reproduce the electrical activity evoked in the cortex by the transcranial magnetic stimulation (TMS); chapter VI presents some preliminary results obtained in the simulation of the neural rhythms associated with memory recall; finally, some general conclusions are drawn in chapter VII.

Ribosome Biogenesis and cell cycle regulation: Effect of RNA Polymerase III inhibition

In cycling cells positive stimuli like nutrient, growth factors and mitogens increase ribosome biogenesis rate and protein synthesis to ensure both growth and proliferation. In contrast, under stress situation, proliferating cells negatively modulate ribosome production to reduce protein synthesis and block cell cycle progression. The main strategy used by cycling cell to coordinate cell proliferation and ribosome biogenesis is to share regulatory elements, which participate directly in ribosome production and in cell cycle regulation. In fact, there is evidence that stimulation or inhibition of cell proliferation exerts direct effect on activity of the RNA polymerases controlling the ribosome biogenesis, while several alterations in normal ribosome biogenesis cause changes of the expression and the activity of the tumor suppressor p53, the main effector of cell cycle progression inhibition. The available data on the cross-talk between ribosome biogenesis and cell proliferation have been until now obtained in experimental model in which changes in ribosome biogenesis were obtained either by reducing the activity of the RNA polymerase I or by down-regulating the expression of the ribosomal proteins. The molecular pathways involved in the relationship between the effect of the inhibition of RNA polymerase III (Pol III) activity and cell cycle progression have been not yet investigated. In eukaryotes, RNA Polymerase III is responsible for transcription of factors involved both in ribosome assembly (5S rRNA) and rRNA processing (RNAse P and MRP).Thus, the aim of this study is characterize the effects of the down-regulation of RNA Polymerase III activity, or the specific depletion of 5S rRNA. The results that will be obtained might lead to a deeper understanding of the molecular pathway that controls the coordination between ribosome biogenesis and cell cycle, and might give useful information about the possibility to target RNA Polymerase III for cancer treatment.

Computational Modeling of Cardiac Excitation-Contraction Coupling in Physiological and Pathological Conditions

The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.

Airway Basal Cell Vascular Endothelial Growth Factor-mediated Cross-Talk Regulates Endothelial Cell Dependent Growth Support of Human Airway Basal Cells

The human airway epithelium is a pseudostratified heterogenous layer comprised of cili-ated, secretory, intermediate and basal cells. As the stem/progenitor population of the airway epi-thelium, airway basal cells differentiate into ciliated and secretory cells to replenish the airway epithelium during physiological turnover and repair. Transcriptome analysis of airway basal cells revealed high expression of vascular endothelial growth factor A (VEGFA), a gene not typically associated with the function of this cell type. Using cultures of primary human airway basal cells, we demonstrate that basal cells express all of the 3 major isoforms of VEGFA (121, 165 and 189) but lack functional expression of the classical VEGFA receptors VEGFR1 and VEGFR2. The VEGFA is actively secreted by basal cells and while it appears to have no direct autocrine function on basal cell growth and proliferation, it functions in a paracrine manner to activate MAPK signaling cascades in endothelium via VEGFR2 dependent signaling pathways. Using a cytokine- and serum-free co-culture system of primary human airway basal cells and human endothelial cells revealed that basal cell secreted VEGFA activated endothelium to ex-press mediators that, in turn, stimulate and support basal cell proliferation and growth. These data demonstrate novel VEGFA mediated cross-talk between airway basal cells and endothe-lium, the purpose of which is to modulate endothelial activation and in turn stimulate and sustain basal cell growth.