971 resultados para Markov Population Processes


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Thioredoxin interacting protein plays a pivotal role in several important processes of cardiovascular homeostasis by functioning as a biological sensor for biomechanical and oxidative stress. However, the effects of genetic variants in the modulation of arterial stiffness are unknown. In this scenario, the present study evaluated the relationship between the TXNIP rs7212 polymorphism and arterial stiffness. In the overall sample and in the diabetic group, individuals carrying CG + GG genotypes had higher PWV values compared with CC genotype group ( 10.0 vs 9.8 ms(-1), P = 0.03; 12.3 vs 11.2 ms(-1), P = 0.01; respectively). Our findings indicated that the G allele may contribute to increased arterial stiffness in the Brazilian general population and suggest a possible interaction with diabetes.

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We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.

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Habitat loss and fragmentation have a prominent role in determining the size of plant populations, and can affect plant-pollinator interactions. It is hypothesized that in small plant populations the ability to set seeds can be reduced due to limited pollination services, since individuals in small populations can receive less quantity or quality of visits. In this study, I investigated the effect of population size on plant reproductive success and insect visitation in 8 populations of two common species in the island of Lesvos, Greece (Mediterranean Sea), Echium plantagineum and Ballota acetabulosa, and of a rare perennial shrub endemic to north-central Italy, Ononis masquillierii. All the three species depended on insect pollinators for sexual reproduction. For each species, pollen limitation was present in all or nearly all populations, but the relationship between pollen limitation and population size was only present in Ononis masquillierii. However, in Echium plantagineum, significant relationships between both open-pollinated and handcrossed-pollinated seed sets and population size were found, being small populations comparatively less productive than large ones. Additionally, for this species, livestock grazing intensity was greater for small populations and for sparse patches, and had a negative influence on productivity of the remnant plants. Both Echium plantagineum and Ballota acetabulosa attracted a great number of insects, representing a wide spectrum of pollinators, thereby can be considered as generalist species. For Ballota acetabulosa, the most important pollinators were megachilid female bees, and insect diversity didn’t decrease with decreasing plant population size. By contrast, Ononis masquillierii plants generally received few visits, with flowers specialized on small bees (Lasioglossum spp.), representing the most important insect guild. In Echium plantagineum and Ballota acetabulosa, plants in small and large populations received the same amount of visits per flower, and no differences in the number of intraplant visited flowers were detected. On the contrary, large Ononis populations supported higher amounts of pollinators than small ones. At patch level, high Echium flower density was associated with more and higher quality pollinators. My results indicate that small populations were not subject to reduced pollination services than large ones in Echium plantagineum and Ballota acetabulosa, and suggest that grazing and resource limitation could have a major impact on population fitness in Echium plantagineum. The absence of any size effects in these two species can be explained in the light of their high local abundance, wide habitat specificity, and ability to compete with other co-flowering species for pollinators. By contrast, size represents a key characteristic for both pollination and reproduction in Ononis masquillierii populations, as an increase in size could mitigate the negative effects coming from the disadvantageous reproductive traits of the species. Finally, the widespread occurrence of pollen limitation in the three species may be the result of 1) an ongoing weakening or disruption of plantpollinator interactions derived from ecological perturbations, 2) an adaptive equilibrium in response to stochastic processes, and 3) the presence of unfavourable reproductive traits (for Ononis masquillierii).

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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.

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The question of how we make, and how we should make judgments and decisions has occupied thinkers for many centuries. This thesis has the aim to add new evidences to clarify the brain’s mechanisms for decisions. The cognitive and the emotional processes of social actions and decisions are investigated with the aim to understand which brain areas are mostly involved. Four experimental studies are presented. A specific kind of population is involved in the first study (as well as in study III) concerning patients with lesion of ventromedial prefrontal cortex (vmPFC). This region is collocated in the ventral surface of frontal lobe, and it seems have an important role in social and moral decision in forecasting the negative emotional consequences of choice. In study I, it is examined whether emotions, specifically social emotions subserved by the vmPFC, affect people’s willingness to trust others. In study II is observed how incidental emotions could encourage trusting behaviour, especially when individuals are not aware of emotive stimulation. Study III has the aim to gather a direct psychophysiological evidence, both in healthy and neurologically impaired individuals, that emotions are crucially involved in shaping moral judgment, by preventing moral violations. Study IV explores how the moral meaning of a decision and its subsequent action can modulate the basic component of action such as sense of agency.

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Pollination and seed dispersal are important ecological processes for the regeneration of plant populations and both vectors for gene exchange between plant populations. For my thesis, I studied the pollination ecology of the South African tree Commiphora harveyi (Burseraceae) and compared it with C. guillauminii from Madagascar. Both species have low visitation rates and a low number of pollinating insect species, resulting in a low fruit set. While their pollination ecology is very similar, they differ in their seed dispersal with a low seed dispersal rate in the Malagasy and a high seed dispersal rate in the South African species. This should be reflected in a stronger genetic differentiation among populations in the Malagasy than in the South African species. My results, based on AFLP markers, contradict these expectations, the overall differentiation was lower in the Malagasy (FST = 0.05) than in the South African species (FST = 0.16). However, at a smaller spatial scale (below 3 km), the Malagasy species was genetically more strongly differentiated than the South African species, which was reflected by the high inter-population variance within the sample site (C. guillauminii: 72.2 - 85.5 %; C. harveyi: 8.4 - 14.5 %). This strong differentiation could arise from limited gene flow, which was confirmed by spatial autocorrelation analyses. The shape of the autocorrelogram suggested that gene exchange between individuals occurred only up to 3 km in the Malagasy species, whereas up to 30 km in the South African species. These results on the genetic structure correspond to the expectations based on seed dispersal data. Thus, seed dispersal seems to be a key factor for the genetic structure in plant populations on a local scale.

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In dieser Arbeit geht es um die Schätzung von Parametern in zeitdiskreten ergodischen Markov-Prozessen im allgemeinen und im CIR-Modell im besonderen. Beim CIR-Modell handelt es sich um eine stochastische Differentialgleichung, die von Cox, Ingersoll und Ross (1985) zur Beschreibung der Dynamik von Zinsraten vorgeschlagen wurde. Problemstellung ist die Schätzung der Parameter des Drift- und des Diffusionskoeffizienten aufgrund von äquidistanten diskreten Beobachtungen des CIR-Prozesses. Nach einer kurzen Einführung in das CIR-Modell verwenden wir die insbesondere von Bibby und Sørensen untersuchte Methode der Martingal-Schätzfunktionen und -Schätzgleichungen, um das Problem der Parameterschätzung in ergodischen Markov-Prozessen zunächst ganz allgemein zu untersuchen. Im Anschluss an Untersuchungen von Sørensen (1999) werden hinreichende Bedingungen (im Sinne von Regularitätsvoraussetzungen an die Schätzfunktion) für die Existenz, starke Konsistenz und asymptotische Normalität von Lösungen einer Martingal-Schätzgleichung angegeben. Angewandt auf den Spezialfall der Likelihood-Schätzung stellen diese Bedingungen zugleich lokal-asymptotische Normalität des Modells sicher. Ferner wird ein einfaches Kriterium für Godambe-Heyde-Optimalität von Schätzfunktionen angegeben und skizziert, wie dies in wichtigen Spezialfällen zur expliziten Konstruktion optimaler Schätzfunktionen verwendet werden kann. Die allgemeinen Resultate werden anschließend auf das diskretisierte CIR-Modell angewendet. Wir analysieren einige von Overbeck und Rydén (1997) vorgeschlagene Schätzer für den Drift- und den Diffusionskoeffizienten, welche als Lösungen quadratischer Martingal-Schätzfunktionen definiert sind, und berechnen das optimale Element in dieser Klasse. Abschließend verallgemeinern wir Ergebnisse von Overbeck und Rydén (1997), indem wir die Existenz einer stark konsistenten und asymptotisch normalen Lösung der Likelihood-Gleichung zeigen und lokal-asymptotische Normalität für das CIR-Modell ohne Einschränkungen an den Parameterraum beweisen.

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This thesis addresses the issue of generating texts in the style of an existing author, that also satisfy structural constraints imposed by the genre of the text. Although Markov processes are known to be suitable for representing style, they are difficult to control in order to satisfy non-local properties, such as structural constraints, that require long distance modeling. The framework of Constrained Markov Processes allows to precisely generate texts that are consistent with a corpus, while being controllable in terms of rhymes and meter. Controlled Markov processes consist in reformulating Markov processes in the context of constraint satisfaction. The thesis describes how to represent stylistic and structural properties in terms of constraints in this framework and how this approach can be used for the generation of lyrics in the style of 60 differents authors An evaluation of the desctibed method is provided by comparing it to both pure Markov and pure constraint-based approaches. Finally the thesis describes the implementation of an augmented text editor, called Perec. Perec is intended to improve creativity, by helping the user to write lyrics and poetry, exploiting the techniques presented so far.

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It is well known that many realistic mathematical models of biological systems, such as cell growth, cellular development and differentiation, gene expression, gene regulatory networks, enzyme cascades, synaptic plasticity, aging and population growth need to include stochasticity. These systems are not isolated, but rather subject to intrinsic and extrinsic fluctuations, which leads to a quasi equilibrium state (homeostasis). The natural framework is provided by Markov processes and the Master equation (ME) describes the temporal evolution of the probability of each state, specified by the number of units of each species. The ME is a relevant tool for modeling realistic biological systems and allow also to explore the behavior of open systems. These systems may exhibit not only the classical thermodynamic equilibrium states but also the nonequilibrium steady states (NESS). This thesis deals with biological problems that can be treat with the Master equation and also with its thermodynamic consequences. It is organized into six chapters with four new scientific works, which are grouped in two parts: (1) Biological applications of the Master equation: deals with the stochastic properties of a toggle switch, involving a protein compound and a miRNA cluster, known to control the eukaryotic cell cycle and possibly involved in oncogenesis and with the propose of a one parameter family of master equations for the evolution of a population having the logistic equation as mean field limit. (2) Nonequilibrium thermodynamics in terms of the Master equation: where we study the dynamical role of chemical fluxes that characterize the NESS of a chemical network and we propose a one parameter parametrization of BCM learning, that was originally proposed to describe plasticity processes, to study the differences between systems in DB and NESS.

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Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.

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Toxicant inputs from agriculture, industry and human settlements have been shown to severely affect freshwater ecosystems. Pollution can lead to changes in population genetic patterns through various genetic and stochastic processes. In my thesis, I investigated the impact of anthropogenic stressors on the population genetics of the zebra mussel Dreissena polymorpha. In order to analyze the genetics of zebra mussel populations, I isolated five new highly polymorphic microsatellite loci. Out of those and other already existing microsatellite markers for this species, I established a robust marker set of six microsatellite loci for D. polymorpha. rnMonitoring the biogeographical background is an important requirement when integrating population genetic measures into ecotoxicological studies. I analyzed the biogeographical background of eleven populations in a section of the River Danube (in Hungary and Croatia) and some of its tributaries, and another population in the River Rhine as genetic outgroup. Moreover, I measured abiotic water parameters at the sampling sites and analyzed if they were correlated with the genetic parameters of the populations. The genetic differentiation was basically consistent with the overall biogeographical history of the populations in the study region. However, the genetic diversity of the populations was not influenced by the geographical distance between the populations, but by the environmental factors oxygen and temperature and also by other unidentified factors. I found strong evidence that genetic adaptation of zebra mussel populations to local habitat conditions had influenced the genetic constitution of the populations. Moreover, by establishing the biogeographical baseline of molecular variance in the study area, I laid the foundation for interpreting population genetic results in ecotoxicological experiments in this region.rnIn a cooperation project with the Department of Zoology of the University of Zagreb, I elaborated an integrated approach in biomonitoring with D. polymorpha by combining the analysis techniques of microsatellite analysis, Comet assay and micronucleus test (MNT). This approach was applied in a case study on freshwater contamination by an effluent of a wastewater treatment plant (WWTP) in the River Drava (Croatia) and a complementary laboratory experiment. I assessed and compared the genetic status of two zebra mussel populations from a contaminated and a reference site. Microsatellite analysis suggested that the contaminated population had undergone a genetic bottleneck, caused by random genetic drift and selection, whereas a bottleneck was not detected in the reference population. The Comet assay did not indicate any difference in DNA damage between the two populations, but MNT revealed that the contaminated population had an increased percentage of micronuclei in hemocytes in comparison to the reference population. The laboratory experiment with mussels exposed to municipal wastewater revealed that mussels from the contaminated site had a lower percentage of tail DNA and a higher percentage of micronuclei than the reference population. These differences between populations were probably caused by an overall decreased fitness of mussels from the contaminated site due to genetic drift and by an enhanced DNA repair mechanism due to adaptation to pollution in the source habitat. Overall, the combination of the three biomarkers provided sufficient information on the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization.rnIn my thesis, I could show that the newly established marker set of six microsatellite loci provided reliable and informative data for population genetic analyses of D. polymorpha. The adaptation of the analyzed zebra mussel populations to the local conditions of their habitat had a strong influence on their genetic constitution. We found evidence that the different genetic constitutions of two populations had influenced the outcome of our ecotoxicological experiment. Overall, the integrated approach in biomonitoring gave comprehensive information about the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization and was well practicable in a first case study.

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The EBPR (Enhanced Biological Phosphorus Removal) is a type of secondary treatment in WWTPs (WasteWater Treatment Plants), quite largely used in full-scale plants worldwide. The phosphorus occurring in aquatic systems in high amounts can cause eutrophication and consequently the death of fauna and flora. A specific biomass is used in order to remove the phosphorus, the so-called PAOs (Polyphosphate Accumulating Organisms) that accumulate the phosphorus in form of polyphosphate in their cells. Some of these organisms, the so-called DPAO (Denitrifying Polyphosphate Accumulating Organisms) use as electron acceptor the nitrate or nitrite, contributing in this way also to the removal of these compounds from the wastewater, but there could be side reactions leading to the formation of nitrous oxides. The aim of this project was to simulate in laboratory scale a EBPR, acclimatizing and enriching the specialized biomass. Two bioreactors were operated as Sequencing Batch Reactors, one enriched in Accumulibacter, the other in Tetrasphaera (both PAOs): Tetrasphaera microorganisms are able to uptake aminoacids as carbon source, Accumulibacter uptake organic carbon (volatile fatty acids, VFA). In order to measure the removal of COD, phosphorus and nitrogen-derivate compounds, different analysis were performed: spectrophotometric measure of phosphorus, nitrate, nitrite and ammonia concentrations, TOC (Total Organic Carbon, measuring the carbon consumption), VFA via HPLC (High Performance Liquid Chromatography), total and volatile suspended solids following standard methods APHA, qualitative microorganism population via FISH (Fluorescence In Situ Hybridization). Batch test were also performed to monitor the NOx production. Both specialized populations accumulated as a result of SBR operations; however, Accumulibacter were found to uptake phosphates at higher extents. Both populations were able to remove efficiently nitrates and organic compounds occurring in the feeding. The experimental work was carried out at FCT of Universidade Nova de Lisboa (FCT-UNL) from February to July 2014.

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Scopo della modellizzazione delle stringhe di DNA è la formulazione di modelli matematici che generano sequenze di basi azotate compatibili con il genoma esistente. In questa tesi si prendono in esame quei modelli matematici che conservano un'importante proprietà, scoperta nel 1952 dal biochimico Erwin Chargaff, chiamata oggi "seconda regola di Chargaff". I modelli matematici che tengono conto delle simmetrie di Chargaff si dividono principalmente in due filoni: uno la ritiene un risultato dell'evoluzione sul genoma, mentre l'altro la ipotizza peculiare di un genoma primitivo e non intaccata dalle modifiche apportate dall'evoluzione. Questa tesi si propone di analizzare un modello del secondo tipo. In particolare ci siamo ispirati al modello definito da da Sobottka e Hart. Dopo un'analisi critica e lo studio del lavoro degli autori, abbiamo esteso il modello ad un più ampio insieme di casi. Abbiamo utilizzato processi stocastici come Bernoulli-scheme e catene di Markov per costruire una possibile generalizzazione della struttura proposta nell'articolo, analizzando le condizioni che implicano la validità della regola di Chargaff. I modelli esaminati sono costituiti da semplici processi stazionari o concatenazioni di processi stazionari. Nel primo capitolo vengono introdotte alcune nozioni di biologia. Nel secondo si fa una descrizione critica e prospettica del modello proposto da Sobottka e Hart, introducendo le definizioni formali per il caso generale presentato nel terzo capitolo, dove si sviluppa l'apparato teorico del modello generale.

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The aim of this study was to investigate the interconnection between the processes of proliferation, dedifferentiation, and intrinsic redifferentiation (chondrogenic) capacities of human articular chondrocyte (HAC), and to identify markers linking HAC dedifferentiation status with their chondrogenic potential. Cumulative population doublings (PD) of HAC expanded in monolayer culture were determined, and a threshold range of 3.57-4.19 PD was identified as indicative of HAC loss of intrinsic chondrogenic capacity in pellets incubated without added chondrogenic factors. While several specific gene and surface markers defined early HAC dedifferentiation process, no clear correlation with the loss of intrinsic chondrogenic potential could be established. CD90 expression during HAC monolayer culture revealed two subpopulations, with sorted CD90-negative cells showing lower proliferative capacity and higher chondrogenic potential compared to CD90-positive cells. Although these data further validated PD as critical for in vitro chondrogenesis, due to the early shift in expression, CD90 could not be considered for predicting chondrogenic potential of HAC expanded for several weeks. In contrast, an excellent mathematically modeled correlation was established between PD and the decline of HAC expressing the intracellular marker S100, providing a direct link between the number of cell divisions and dedifferentiation/loss of intrinsic chondrogenic capacity. Based on the dynamics of S100-positive HAC during expansion, we propose asymmetric cell division as a potential mechanism of HAC dedifferentiation, and S100 as a marker to assess chondrogenicity of HAC during expansion, of potential value for cell-based cartilage repair treatments.

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Screening people without symptoms of disease is an attractive idea. Screening allows early detection of disease or elevated risk of disease, and has the potential for improved treatment and reduction of mortality. The list of future screening opportunities is set to grow because of the refinement of screening techniques, the increasing frequency of degenerative and chronic diseases, and the steadily growing body of evidence on genetic predispositions for various diseases. But how should we decide on the diseases for which screening should be done and on recommendations for how it should be implemented? We use the examples of prostate cancer and genetic screening to show the importance of considering screening as an ongoing population-based intervention with beneficial and harmful effects, and not simply the use of a test. Assessing whether screening should be recommended and implemented for any named disease is therefore a multi-dimensional task in health technology assessment. There are several countries that already use established processes and criteria to assess the appropriateness of screening. We argue that the Swiss healthcare system needs a nationwide screening commission mandated to conduct appropriate evidence-based evaluation of the impact of proposed screening interventions, to issue evidence-based recommendations, and to monitor the performance of screening programmes introduced. Without explicit processes there is a danger that beneficial screening programmes could be neglected and that ineffective, and potentially harmful, screening procedures could be introduced.