Next-Generation Sequencing-Based Mutations Scanning Strategy of the BCR-ABL Kinase Domain in Patients with PhiladelPhia-Chromosome Positive Leukemias Treated with Tyrosine Kinase Inhibitors

In chronic myeloid leukemia and Philadelphia-positive acute lymphoblastic leukemia patients resistant to tyrosine kinase inhibitors (TKIs), BCR-ABL kinase domain mutation status is an essential component of the therapeutic decision algorithm. The recent development of Ultra-Deep Sequencing approach (UDS) has opened the way to a more accurate characterization of the mutant clones surviving TKIs conjugating assay sensitivity and throughput. We decided to set-up and validated an UDS-based for BCR-ABL KD mutation screening in order to i) resolve qualitatively and quantitatively the complexity and the clonal structure of mutated populations surviving TKIs, ii) study the dynamic of expansion of mutated clones in relation to TKIs therapy, iii) assess whether UDS may allow more sensitive detection of emerging clones, harboring critical 2GTKIs-resistant mutations predicting for an impending relapse, earlier than SS. UDS was performed on a Roche GS Junior instrument, according to an amplicon sequencing design and protocol set up and validated in the framework of the IRON-II (Interlaboratory Robustness of Next-Generation Sequencing) International consortium.Samples from CML and Ph+ ALL patients who had developed resistance to one or multiple TKIs and collected at regular time-points during treatment were selected for this study. Our results indicate the technical feasibility, accuracy and robustness of our UDS-based BCR-ABL KD mutation screening approach. UDS was found to provide a more accurate picture of BCR-ABL KD mutation status, both in terms of presence/absence of mutations and in terms of clonal complexity and showed that BCR-ABL KD mutations detected by SS are only the “tip of iceberg”. In addition UDS may reliably pick 2GTKIs-resistant mutations earlier than SS in a significantly greater proportion of patients.The enhanced sensitivity as well as the possibility to identify low level mutations point the UDS-based approach as an ideal alternative to conventional sequencing for BCR-ABL KD mutation screening in TKIs-resistant Ph+ leukemia patients

Climate impact studies of sediment transport on the Adriatic coastal zone

The study of the impact of climate change on the environment has been based, until very recently, on an global approach, whose interest from a local point of view is very limited. This thesis, on the contrary, has treated the study of the impact of climate change in the Adriatic Sea basin following a twofold strategy of regionalization and integration of numerical models in order to reproduce the present and future scenarios of the system through a more and more realistic and solid approach. In particular the focus of the study was on the impact on the physical environment and on the sediment transport in the basin. This latter is a very new and original issue, to our knowledge still uninvestigated. The study case of the coastal area of Montenegro was particularly studied, since it is characterized by an important supply of sediment through the Buna/Bojana river, second most important in the Adriatic basin in terms of flow. To do this, a methodology to introduce the tidal processes in a baroclinic primitive equations Ocean General Circulation Model was applied and tidal processes were successfully reproduced in the Adriatic Sea, analyzing also the impacts they have on the mean general circulation, on salt and heat transport and on mixing and stratification of the water column in the different seasons of the year. The new hydrodynamical model has been further coupled with a wave model and with a river and sea sediment transport model, showing good results in the reproduction of sediment transport processes. Finally this complex coupled platform was integrated in the period 2001-2030 under the A1B scenario of IPCC, and the impact of climate change on the physical system and on sediment transport was preliminarily evaluated.

Models and Algorihtm for the Optimization of Real-World Routing and Logistics Problems

Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solve them by means of exact and heuristic methods. We treat three classes of real-world routing and logistics problems. We deal with one of the most important tactical problems that arises in the managing of the bike sharing systems, that is the Bike sharing Rebalancing Problem (BRP). We propose models and algorithms for real-world earthwork optimization problems. We describe the 3DP process and we highlight several optimization issues in 3DP. Among those, we define the problem related to the tool path definition in the 3DP process, the 3D Routing Problem (3DRP), which is a generalization of the arc routing problem. We present an ILP model and several heuristic algorithms to solve the 3DRP.

Genome-wide analysis of G-type lectin genes in Fragaria vesca and functional characterization of FaMBL1 gene in defense response of F. × ananassa to fungal pathogens

Strawberry (Fragaria × ananassa) is an important soft fruit but easily to be infected by pathogens. Anthracnose and gray mold are two of the most destructive diseases of strawberry which lead to serious fruit rot. The first chapter introduced strawberry anthracnose caused by Colletotrichum acutatum. The infection strategy, disease cycle and management of C. acutatum on strawberry were reported. Likewise, the second chapter summarized the infection strategy of Botrytis cinerea and the defense responses of strawberry. As we already know white unripe strawberry fruits are more resistant to C. acutatum than red ripe fruits. During the interaction between strawberry white/red fruit and C. acutaum, a mannose binding lectin gene, FaMBL1, was found to be the most up-regulated gene and induced exclusively in white fruit. FaMBL1 belongs to the G-type lectin family which has important roles in plant development and defense process. To get insight into the role of FaMBL1, genome-wide identification was carried out on G-type lectin gene family in Fragaria vesca and the results were showed in chapter 3. G-type lectin genes make up a large family in F. vesca. Active expression upon biotic/abiotic stresses suggested a potential role of G-lectin genes in strawberry defenses. Hence, stable transgenic strawberry plants with FaMBL1 gene overexpressed were generated. Transformed strawberry plants were screened and identified. The results were showed in chapter 4, content of disease-related phytohormone, jasmonic acid, was found decreased in overexpressing lines compared with wild type (WT). Petioles inoculated by C. fioriniae of overexpressing lines had lower disease incidence than WT. Leaves of overexpressing lines challenged by B. cinerea showed remarkably smaller lesion diameters compared with WT. The chitinase 2-1 (FaChi2-1) showed higher expression in overexpressing lines than in WT during the interaction with B. cinerea, which could be related with the lower susceptibility of overexpressing lines.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.

Development and food security in africa from the 1960s to 2010s: the case of Ethiopia

Persistent food insecurity and famines have continued to significantly shape the development policies of Ethiopia for decades. Over the decades, frequent famines caused not only the death of hundreds of thousands of victims but also significantly contributed to two revolutions that swept away the Haile Selassie and Derg regimes, as well as significantly taxing the legitimacy of the incumbent regime. As a result, agriculture and food security have become increasingly the top policy priorities for all political regimes in Ethiopia. However, the development policies of the ruling elites of Ethiopia have consistently failed to transform backward agriculture and ensure food security. The failures of the development policies of the Ethiopian governments over the years were attributed to several factors. Ethiopian authoritarian politics, centralized rule with a lack of transparency and accountability; the isolation of peasants from the development and governance process, and the lack of coherent agricultural development strategies that invest in peasant agriculture and create synergy among sectors are identified as key issues that have contributed to the persistence of food insecurity in the country. The literature on the failure of Ethiopia's political regimes to address food insecurity and famine has two major gaps that this study aims to fill. First, the cumulative and path-dependent food security and agricultural development policy environment were not adequately considered. Second, the strategy of extraversion by subsequent political regimes to use external support as a relief to prevent the famine-induced political crisis. This study used a mixed approach to collect data and present the evolution of the interplays of development policies and food security in three regimes within the context of international food security discourses. This study found out how the historical patterns of approaches of Ethiopia’s regimes to development and governance led to frequent famines and persistent food insecurity.

Mars delivery service - development of the electro-mechanical systems of the Sample Fetch Rover for the Mars Sample Return Campaign

This thesis describes the development of the Sample Fetch Rover (SFR), studied for Mars Sample Return (MSR), an international campaign carried out in cooperation between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The focus of this document is the design of the electro-mechanical systems of the rover. After placing this work into the general context of robotic planetary exploration and summarising the state of the art for what concerns Mars rovers, the architecture of the Mars Sample Return Campaign is presented. A complete overview of the current SFR architecture is provided, touching upon all the main subsystems of the spacecraft. For each area, it is discussed what are the design drivers, the chosen solutions and whether they use heritage technology (in particular from the ExoMars Rover) or new developments. This research focuses on two topics of particular interest, due to their relevance for the mission and the novelty of their design: locomotion and sample acquisition, which are discussed in depth. The early SFR locomotion concepts are summarised, covering the initial trade-offs and discarded designs for higher traverse performance. Once a consolidated architecture was reached, the locomotion subsystem was developed further, defining the details of the suspension, actuators, deployment mechanisms and wheels. This technology is presented here in detail, including some key analysis and test results that support the design and demonstrate how it responds to the mission requirements. Another major electro-mechanical system developed as part of this work is the one dedicated to sample tube acquisition. The concept of operations of this machinery was defined to be robust against the unknown conditions that characterise the mission. The design process led to a highly automated robotic system which is described here in its main components: vision system, robotic arm and tube storage.

Orchestration of multiscale model for computational oncology

Cancer is a challenging disease that involves multiple types of biological interactions in different time and space scales. Often computational modelling has been facing problems that, in the current technology level, is impracticable to represent in a single space-time continuum. To handle this sort of problems, complex orchestrations of multiscale models is frequently done. PRIMAGE is a large EU project that aims to support personalized childhood cancer diagnosis and prognosis. The goal is to do so predicting the growth of the solid tumour using multiscale in-silico technologies. The project proposes an open cloud-based platform to support decision making in the clinical management of paediatric cancers. The orchestration of predictive models is in general complex and would require a software framework that support and facilitate such task. The present work, proposes the development of an updated framework, referred herein as the VPH-HFv3, as a part of the PRIMAGE project. This framework, a complete re-writing with respect to the previous versions, aims to orchestrate several models, which are in concurrent development, using an architecture as simple as possible, easy to maintain and with high reusability. This sort of problem generally requires unfeasible execution times. To overcome this problem was developed a strategy of particularisation, which maps the upper-scale model results into a smaller number and homogenisation which does the inverse way and analysed the accuracy of this approach.