Definition, realization and evaluation of a software reference architecture for use in space applications

A recent initiative of the European Space Agency (ESA) aims at the definition and adoption of a software reference architecture for use in on-board software of future space missions. Our PhD project placed in the context of that effort. At the outset of our work we gathered all the industrial needs relevant to ESA and all the main European space stakeholders and we were able to consolidate a set of technical high-level requirements for the fulfillment of them. The conclusion we reached from that phase confirmed that the adoption of a software reference architecture was indeed the best solution for the fulfillment of the high-level requirements. The software reference architecture we set on building rests on four constituents: (i) a component model, to design the software as a composition of individually verifiable and reusable software units; (ii) a computational model, to ensure that the architectural description of the software is statically analyzable; (iii) a programming model, to ensure that the implementation of the design entities conforms with the semantics, the assumptions and the constraints of the computational model; (iv) a conforming execution platform, to actively preserve at run time the properties asserted by static analysis. The nature, feasibility and fitness of constituents (ii), (iii) and (iv), were already proved by the author in an international project that preceded the commencement of the PhD work. The core of the PhD project was therefore centered on the design and prototype implementation of constituent (i), a component model. Our proposed component model is centered on: (i) rigorous separation of concerns, achieved with the support for design views and by careful allocation of concerns to the dedicated software entities; (ii) the support for specification and model-based analysis of extra-functional properties; (iii) the inclusion space-specific concerns.

A SMO inhibitor drug reduces the progenitor cell's maintenance in the Drosophila hematopoietic organ: a novel model to study Chronic Myelogenous Leukemia relapse

The chronic myeloid leukemia complexity and the difficulties of disease eradication have recently led to the development of drugs which, together with the inhibitors of TK, could eliminate leukemia stem cells preventing the occurrence of relapses in patients undergoing transplantation. The Hedgehog (Hh) signaling pathway positively regulates the self-renewal and the maintenance of leukemic stem cells and not, and this function is evolutionarily conserved. Using Drosophila as a model, we studied the efficacy of the SMO inhibitor drug that inhibit the human protein Smoothened (SMO). SMO is a crucial component in the signal transduction of Hh and its blockade in mammals leads to a reduction in the disease induction. Here we show that administration of the SMO inhibitor to animals has a specific effect directed against the Drosophila ortholog protein, causing loss of quiescence and hematopoietic precursors mobilization. The SMO inhibitor induces in L3 larvae the appearance of melanotic nodules generated as response by Drosophila immune system to the increase of its hemocytes. The same phenotype is induced even by the dsRNA:SMO specific expression in hematopoietic precursors of the lymph gland. The drug action is also confirmed at cellular level. The study of molecular markers has allowed us to demonstrate that SMO inhibitor leads to a reduction of the quiescent precursors and to an increase of the differentiated cells. Moreover administering the inhibitor to heterozygous for a null allele of Smo, we observe a significant increase in the phenotype penetrance compared to administration to wild type animals. This helps to confirm the specific effect of the drug itself. These data taken together indicate that the study of inhibitors of Smo in Drosophila can represent a useful way to dissect their action mechanism at the molecular-genetic level in order to collect information applicable to the studies of the disease in humans.

IGF system, CD99 and tumor-specific chromosomal translocations: evaluation of their cross-talk and definition of their role in Ewing sarcoma and prostate cancer

Aberrant expression of ETS transcription factors, including FLI1 and ERG, due to chromosomal translocations has been described as a driver event in initiation and progression of different tumors. In this study, the impact of prostate cancer (PCa) fusion gene TMPRSS2-ERG was evaluated on components of the insulin-like growth factor (IGF) system and the CD99 molecule, two well documented targets of EWS-FLI1, the hallmark of Ewing sarcoma (ES). The aim of this study was to identify common or distinctive ETS-related mechanisms which could be exploited at biological and clinical level. The results demonstrate that IGF-1R represents a common target of ETS rearrangements as ERG and FLI1 bind IGF-1R gene promoter and their modulation causes alteration in IGF-1R protein levels. At clinical level, this mechanism provides basis for a more rationale use of anti-IGF-1R inhibitors as PCa cells expressing the fusion gene better respond to anti-IGF-1R agents. EWS-FLI1/IGF-1R axis provides rationale for combination of anti-IGF-1R agents with trabectedin, an alkylator agent causing enhanced EWS-FLI1 occupancy on the IGF-1R promoter. TMPRSS2-ERG also influences prognosis relevance of IGF system as high IGF-1R correlates with a better biochemical progression free survival (BPFS) in PCa patients negative for the fusion gene while marginal or no association was found in the total cases or TMPRSS2-ERG-positive cases, respectively. This study indicates CD99 is differentially regulated between ETS-related tumors as CD99 is not a target of ERG. In PCa, CD99 did not show differential expression between TMPRSS2-ERG-positive and –negative cells. A direct correlation was anyway found between ERG and CD99 proteins both in vitro and in patients putatively suggesting that ERG target genes comprehend regulators of CD99. Despite a little trend suggesting a correlation between CD99 expression and a better BPFS, no clinical relevance for CD99 was found in the field of prognostic biomarkers.

Definition of Food Safety Criteria for Bacteria Food-Borne Pathogens in Ready to Eat products

The aims of this research study is to explore the opportunity to set up Performance Objectives (POs) parameters for specific risks in RTE products to propose for food industries and food authorities. In fact, even if microbiological criteria for Salmonella and Listeria monocytogenes Ready-to-Eat (RTE) products are included in the European Regulation, these parameters are not risk based and no microbiological criteria for Bacillus cereus in RTE products is present. For these reasons the behaviour of Salmonella enterica in RTE mixed salad, the microbiological characteristics in RTE spelt salad, and the definition of POs for Bacillus cereus and Listeria monocytogenes in RTE spelt salad has been assessed. Based on the data produced can be drawn the following conclusions: 1. A rapid growth of Salmonella enterica may occurr in mixed ingredient salads, and strict temperature control during the production chain of the product is critical. 2. Spelt salad is characterized by the presence of high number of Lactic Acid Bacteria. Listeria spp. and Enterobacteriaceae, on the contrary, did not grow during the shlef life, probably due to the relevant metabolic activity of LAB. 3. The use of spelt and cheese compliant with the suggested POs might significantly reduce the incidence of foodborne intoxications due to Bacillus cereus and Listeria monocytogenes and the proportions of recalls, causing huge economic losses for food companies commercializing RTE products. 4. The approach to calculate the POs values and reported in my work can be easily adapted to different food/risk combination as well as to any changes in the formulation of the same food products. 5. The optimized sampling plans in term of number of samples to collect can be derive in order to verify the compliance to POs values selected.

The mesophotic zone of the Mediterranean Sea: spatial definition, biodiversity, and predictive models

The mesophotic zone is frequently defined as ranging between 30-40 and 150 m depth. However, these borders are necessarily imprecise due to variations in the penetration of light along the water column related to local factors. Moreover, density of data on mesophotic ecosystems vary along geographical distance, with temperate latitudes largely less explored than tropical situations. This is the case of the Mediterranean Sea, where information on mesophotic ecosystems is largely lower with respect to tropical situations. The lack of a clear definition of the borders of the mesophotic zone may represent a problem when information must be transferred to the policy that requires a coherent spatial definition to plan proper management and conservation measures. The present thesis aims at providing information on the spatial definition of the mesophotic zone in the Mediterranean Sea, its biodiversity and distribution of its ecosystems. The first chapter analyzes information on mesophotic ecosystems in the Mediterranean Sea to identify gaps in the literature and map the mesophotic zone in the Mediterranean Sea using light penetration estimated from satellite data. In the second chapter, different visual techniques to study mesophotic ecosystems are compared to identify the best analytical method to estimate diversity and habitat extension. In the third chapter, a set of Remotely Operated vehicles (ROV) surveys performed on mesophotic assemblages in the Mediterranean Sea are analyzed to describe their taxonomic and functional diversity and environmental factors influencing their structure. A Habitat Suitability Model is run in the fourth chapter to map the distribution of areas suitable for the presence of deep-water oyster reefs in the Adriatic-Ionian area. The fifth chapter explores the mesophotic zone in the northern Gulf of Mexico providing its spatial and vertical extension of the mesophotic zone and information on the diversity associated with mesophotic ecosystems.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).