15 resultados para genetic screeing and testing

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Introduction – Although imatinib (IM) is a recognized gold standard in chronic myeloid leukemia (CML) therapy, resistance has emerged in a significant proportion of patients. Aim – The aim of this study was: (1) to investigate the role of genetic variants in genes encoding for IM transporters, as candidate of IM responsiveness and (2) to test the influence of miRNAs on IM response, focusing on efflux transporters. Methods – As a first step, a panel of polymorphisms (SNPs) was genotyped in a subgroup population of 189 patients enrolled in the Tyrosine Kinase Inhibitor Optimization and Selectivity (TOPS) trial. The association with cytogenetic response and molecular response (MR) was assessed for each SNP. As a second step, an in vitro IM-resistant model (K-562 CML cell line) was established. miRNAs profiles were analyzed using Taqman arrays and in silico search was performed for miRNAs deregulated after IM treatment. mRNA and protein expression were quantified using TaqMan realtime PCR and Western blotting, respectively. Results – (1) Among Caucasian patients, ABCB1 rs60023214 significantly correlated with complete MR (P = 0.005). Concerning SNPs combination in IM uptake transporters, the associations with treatment outcomes were statistically significant for both major and complete MR (P = 0.005 and P = 0.01, respectively). (2) ABCB1 protein was not expressed under any conditions of treatment, differently from ABCG2. Two deregulated miRNAs, namely miR-212 and miR-328, were identified to be inversely correlated with ABCG2 (r2= 0.57; p=0.03 and r2=0.47; p=0.06, respectively). Experiments of loss and gain of function confirmed the functional influence of these miRNAs on ABCG2. Conclusion – The multiple candidate gene approach identified single and combination of SNPs that can be proposed as predictor of IM response. The in vitro study suggested that IM resistance could be mediated by miRNA-dependent mechanism. Further studies are needed to validate these preliminary findings.

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Oncolytic virotherapy exploits the ability of viruses to infect and kill cells. It is suitable as treatment for tumors that are not accessible by surgery and/or respond poorly to the current therapeutic approach. HSV is a promising oncolytic agent. It has a large genome size able to accommodate large transgenes and some attenuated oncolytic HSVs (oHSV) are already in clinical trials phase I and II. The aim of this thesis was the generation of HSV-1 retargeted to tumor-specific receptors and detargeted from HSV natural receptors, HVEM and Nectin-1. The retargeting was achieved by inserting a specific single chain antibody (scFv) for the tumor receptor selected inside the HSV glycoprotein gD. In this research three tumor receptors were considered: epidermal growth factor receptor 2 (HER2) overexpressed in 25-30% of breast and ovarian cancers and gliomas, prostate specific membrane antigen (PSMA) expressed in prostate carcinomas and in neovascolature of solid tumors; and epidermal growth factor receptor variant III (EGFRvIII). In vivo studies on HER2 retargeted viruses R-LM113 and R-LM249 have demonstrated their high safety profile. For R-LM249 the antitumor efficacy has been highlighted by target-specific inhibition of the growth of human tumors in models of HER2-positive breast and ovarian cancer in nude mice. In a murine model of HER2-positive glioma in nude mice, R-LM113 was able to significantly increase the survival time of treated mice compared to control. Up to now, PSMA and EGFRvIII viruses (R-LM593 and R-LM613) are only characterized in vitro, confirming the specific retargeting to selected targets. This strategy has proved to be generally applicable to a broad spectrum of receptors for which a single chain antibody is available.

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Through modelling activity, experimental campaigns, test bench and on-field validation, a complete powertrain for a BEV has been designed, assembled and used in a motorsport competition. The activity can be split in three main subjects, representing the three key components of an BEV vehicle. First of all a model of the entire powertrain has been developed in order to understand how the various design choices will influence the race lap-time. The data obtained was then used to design, build and test a first battery pack. After bench tests and track tests, it was understood that by using all the cell charac-teristics, without breaking the rules limitations, higher energy and power densities could have been achieved. An updated battery pack was then designed, produced and raced with at Motostudent 2018 re-sulting in a third place at debut. The second topic of this PhD was the design of novel inverter topologies. Three inverters have been de-signed, two of them using Gallium Nitride devices, a promising semiconductor technology that can achieve high switching speeds while maintaining low switching losses. High switching frequency is crucial to reduce the DC-Bus capacitor and then increase the power density of 3 phase inverters. The third in-verter uses classic Silicon devices but employs a ZVS (Zero Voltage Switching) topology. Despite the in-creased complexity of both the hardware and the control software, it can offer reduced switching losses by using conventional and established silicon mosfet technology. Finally, the mechanical parts of a three phase permanent magnet motor have been designed with the aim to employ it in UniBo Motorsport’s 2020 Formula Student car.

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The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.

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The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

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This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

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ABSTRACT Background:Strong opioids are the treatment of choice for moderate to severe cancer-related pain. Fentanyl is a synthetic opioid with high affinity for the μ-opioid receptor and is 75–100 times more potent than morphine. Fentanyl is metabolised rapidly, particularly in the liver and only 10% is excreted as intact substance. The use of CYP3A4 inhibitors and inducers, impaired liver function, and heating of the patch potentially influence fentanyl pharmacokinetics in a clinically relevant way. The influence of BMI and gender on fentanyl pharmacokinetics is questionable. Pharmacogenetic, may influence fentanyl pharmacokinetic and other factors have been studied but did not show significant and clinically relevant effects on fentanyl pharmacokinetic. Method: This is a biological interventional prospective, single-center study in 49 patients with solid or haematological neoplasm treated with transdermal fentanyl undergoing 5-step pharmacokinetic and pharmacogenetic withdrawals from administration of the fentanyl patch. Objective:to evaluate the pharmacokinetic and pharmacogenetic of transdermal fentanyl in relation to the patient's clinical response on pain Results: Sex was the only parameter with evidence of different distribution between responders and non-responders , showing a major chance for male to be responders than females. We found some correlation with pharmacokinetic parameters and sex, regarding adverse events and NRS correlation with BPI. NAT2 and UGT2B7 polymorphisms are associated with AUC and Cmax kinetics parameters, NAT2 and CYP4F2 showed some evidence of association with the fentanyl dosage and CYP2B6 polymorphism seemed to be correlate with side effects. Conclusion: Small sample size of study population make difficult do find some significant correlation between pharmacogenetic, pharmacokinetic and clinical response. Larger studies are needed to increase knowledge about response to opioid treatment in cancer patients to better individualized pain treatment.

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Honey bees are considered keystone species in ecosystem, the effect of harmful pesticides for the honey bees, the action of extreme climatic waves and their consequence on honey bees health can cause the loss of many colonies which could contribute to the reduction of the effective population size and incentive the use of non-autochthonous queens to replace dead colonies. Over the last decades, the use of non-ligustica bee subspecies in Italy has increased and together with the mentioned phenomena exposed native honey bees to hybridization, laeding to a dramatic loss of genetic erosion and admixture. Healthy genetic diversity within honey bee populations is critical to provide tolerance and resistance to current and future threatening. Nowadays it is urgent to design strategies for the conservation of local subspecies and their valorisation on a productive scale. In this Thesis we applied genomics tool for the analysis of the genetic diversity and the genomic integrity of honey bee populations in Italy are described. In this work mtDNA based methods are presented using honey bee DNA or honey eDNA as source of information of the genetic diversity of A. mellifera at different level. Taken together, the results derived from these studies should enlarge the knowledge of the genetic diversity and integrity of the honey bee populations in Italy, filling the gap of information necessary to design efficient conservation programmes. Furthermore, the methods presented in these works will provide a tool for the honey authentication to sustain and valorise beekeeping products and sector against frauds.

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In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

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AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

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In this study we have analysed the genetic variability in ca. 700 samples belonging to six species of genus Lepus using maternal and biparental molecular markers (mitochondrial DNA, microsatellites, Single Nucleotide Polimorphisms). We aimed to reconstruct the phylogenetic relationships of species of hares living in Europe, and assess the occurrence of hybridization between the European hare Lepus europaeus and the Italian hare Lepus corsicanus. Results showed a deep genetic differentiation and absence of hybridization between L. corsicanus and L. europaeus, confirming that they are distinct and distantly related biological species. In contrast, we showed small genetic distances and a close phylogenetic relationship between the Italian hare and Cantabrian hare L. castroviejoi, which suggest a deeper evaluation of their taxonomic status. Populations of L. corsicanus are geographically differentiated. In particular, the peninsular and Sicilian populations of Italian hares are sharply genetically distinct, which calls for avoiding any translocation between Italy and Sicily. Information on genetic variability and population structure is being used to implement the Italian Action Plan for L. corsicanus.

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The interaction between disciplines in the study of human population history is of primary importance, profiting from the biological and cultural characteristics of humankind. In fact, data from genetics, linguistics, archaeology and cultural anthropology can be combined to allow for a broader research perspective. This multidisciplinary approach is here applied to the study of the prehistory of sub-Saharan African populations: in this continent, where Homo sapiens originally started his evolution and diversification, the understanding of the patterns of human variation has a crucial relevance. For this dissertation, molecular data is interpreted and complemented with a major contribution from linguistics: linguistic data are compared to the genetic data and the research questions are contextualized within a linguistic perspective. In the four articles proposed, we analyze Y chromosome SNPs and STRs profiles and full mtDNA genomes on a representative number of samples to investigate key questions of African human variability. Some of these questions address i) the amount of genetic variation on a continental scale and the effects of the widespread migration of Bantu speakers, ii) the extent of ancient population structure, which has been lost in present day populations, iii) the colonization of the southern edge of the continent together with the degree of population contact/replacement, and iv) the prehistory of the diverse Khoisan ethnolinguistic groups, who were traditionally understudied despite representing one of the most ancient divergences of modern human phylogeny. Our results uncover a deep level of genetic structure within the continent and a multilayered pattern of contact between populations. These case studies represent a valuable contribution to the debate on our prehistory and open up further research threads.

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Acute myocardial infarction (AMI) is a multifactorial disease with a complex pathogenesis where lifestyle, individual genetic background and environmental risk factors are involved. Altered inflammatory responses seems to be implicated in the pathogenesis of atherosclerosis. To understand which genes may predispose to increased risk of cardiovascular disease gene polymorphism of immune regulatory genes, and clinical events from the Offs of parents with an early AMI were investigated. Genetics data from Offs were compared with those obtained from healthy subjects and an independent cohort of patients with clinical sporadic AMI. Rates of clinical events during a 24 years follow up from Offs and from an independent Italian population survey were also evaluated. This study showed that a genetic signature consisting of the concomitant presence of the CC genotype of VEGF, the A allele of IL-10 and the A allele of IFN-γ was indeed present in the Offs population. During the 24-year follow-up, Offs with a positive familiarity in spite of a relatively young age showed an increased prevalence of diabetes, ischemic heart disease and stroke. In these patients with the genetic signature the EBV and HHV-6 herpes virus were also investigated and founded. These findings reinforce the notion that subjects with a familial history of AMI are at risk of an accelerated aging of cardiovascular system resulting in cardiovascular events. These data suggest that selected genes with immune regulatory functions and envoronmental factors are part of the complex genetic background contributing to familiarity for cardiovascular diseases.N

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Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.