Land use management in mountainous areas: combining ground-based and EO (Earth Observation) data to investigate the shallow landsliding susceptibility in the Duron valley (Trento, Italy).

Throughout the alpine domain, shallow landslides represent a serious geologic hazard, often causing severe damages to infrastructures, private properties, natural resources and in the most catastrophic events, threatening human lives. Landslides are a major factor of landscape evolution in mountainous and hilly regions and represent a critical issue for mountainous land management, since they cause loss of pastoral lands. In several alpine contexts, shallow landsliding distribution is strictly connected to the presence and condition of vegetation on the slopes. With the aid of high-resolution satellite images, it's possible to divide automatically the mountainous territory in land cover classes, which contribute with different magnitude to the stability of the slopes. The aim of this research is to combine EO (Earth Observation) land cover maps with ground-based measurements of the land cover properties. In order to achieve this goal, a new procedure has been developed to automatically detect grass mantle degradation patterns from satellite images. Moreover, innovative surveying techniques and instruments are tested to measure in situ the shear strength of grass mantle and the geomechanical and geotechnical properties of these alpine soils. Shallow landsliding distribution is assessed with the aid of physically based models, which use the EO-based map to distribute the resistance parameters across the landscape.

NMR Based Foodomics to Investigate the Digestibility of Protein-Rich Food Products

Nowadays, in developed countries, the excessive food intake, in conjunction with a decreased physical activity, has led to an increase in lifestyle-related diseases, such as obesity, cardiovascular diseases, type -2 diabetes, a range of cancer types and arthritis. The socio-economic importance of such lifestyle-related diseases has encouraged countries to increase their efforts in research, and many projects have been initiated recently in research that focuses on the relationship between food and health. Thanks to these efforts and to the growing availability of technologies, the food companies are beginning to develop healthier food. The necessity of rapid and affordable methods, helping the food industries in the ingredient selection has stimulated the development of in vitro systems that simulate the physiological functions to which the food components are submitted when administrated in vivo. One of the most promising tool now available appears the in vitro digestion, which aims at predicting, in a comparative way among analogue food products, the bioaccessibility of the nutrients of interest.. The adoption of the foodomics approach has been chosen in this work to evaluate the modifications occurring during the in vitro digestion of selected protein-rich food products. The measure of the proteins breakdown was performed via NMR spectroscopy, the only techniques capable of observing, directly in the simulated gastric and duodenal fluids, the soluble oligo- and polypeptides released during the in vitro digestion process. The overall approach pioneered along this PhD work, has been discussed and promoted in a large scientific community, with specialists networked under the INFOGEST COST Action, which recently released a harmonized protocol for the in vitro digestion. NMR spectroscopy, when used in tandem with the in vitro digestion, generates a new concept, which provides an additional attribute to describe the food quality: the comparative digestibility, which measures the improvement of the nutrients bioaccessibility.

The foodomics approach to investigate the impact of the matrix structure on food quality: applications of magnetic resonance spectroscopy, relaxometry and imaging

The aim of this thesis is to explore the possible influence of the food matrix on food quality attributes. Using nuclear magnetic resonance techniques, the matrix-dependent properties of different foods were studied and some useful indices were defined to classify food products based on the matrix behaviour when responding to processing phenomena. Correlations were found between fish freshness indices, assessed by certain geometric parameters linked to the morphology of the animal, i.e. a macroscopic structure, and the degradation of the product structure. The same foodomics approach was also applied to explore the protective effect of modified atmospheres on the stability of fish fillets, which are typically susceptible to oxidation of the polyunsaturated fatty acids incorporated in the meat matrix. Here, freshness is assessed by evaluating the time-dependent change in the fish metabolome, providing an established freshness index, and its relationship to lipid oxidation. In vitro digestion studies, focusing on food products with different matrixes, alone and in combination with other meal components (e.g. seasoning), were conducted to investigate possible interactions between enzymes and food, modulated by matrix structure, which influence digestibility. The interaction between water and the gelatinous matrix of the food, consisting of a network of protein gels incorporating fat droplets, was also studied by means of nuclear magnetic relaxometry, in order to create a prediction tool for the correct classification of authentic and counterfeit food products protected by a quality label. This is one of the first applications of an NMR method focusing on the supramolecular structure of the matrix, rather than the chemical composition, to assess food authenticity. The effect of innovative processing technologies, such as PEF applied to fruit products, has been assessed by magnetic resonance imaging, exploiting information associated with the rehydration kinetics exerted by a modified food structure.

Genes involved in germline regulative pathways in metazoa: an integrative approach to investigate a key feature of animal biology

In Metazoa, the germline represents the cell lineage devoted to transmission of genetic heredity across generations. Its functions intuitively evoke the crucial roles that it plays in the development of a new organism and in the evolution of the species. Germline establishment is tightly tied to animal multicellularity itself, in which the complex differentiation of cell lineages is favoured by the confinement of totipotency in specific cell populations. In the present thesis, I addressed the subject of germline characterization in animals through different approaches, in an attempt to cover different sides and scales. First, I investigated the extent and nature of shared differentially transcribed molecular factors in 10 different species germline-related lineages. I observed that newly evolved genes are less likely to be involved in germline-related mechanisms and that the mostly shared transcriptional signal across the species considered was the upregulation of genes associated to proper DNA replication, instead of the expected transcriptional and post-transcriptional regulation, that apparently have a higher level of lineage-specificity. I then focused on the evolutionary history of Tudor domain containing proteins, a gene family that underwent germline-associated expansions in animals. Using data from 24 holozoan phyla, I could confirm the previously proposed evolution of the Tudor domain secondary structure. Also, I associated lineage-specific family reductions and expansions to peculiar genomic dynamics and to the evolution of germline-associated piRNA pathway of retrotransposon silencing. Lastly, I characterized and investigated the expression of the Tudor protein TDRD7 in the clam Ruditapes philippinarum. Through immunolocalization, I could compare its expression profiles in gametogenic specimens to the previously characterized germline marker vasa. Combining results with literature, I proposed that, in this species, TDRD7 is involved in the assembly of germ granules, i.e. cytoplasmic structures associated to germline differentiation in virtually all animals, but whose assemblers can be taxon specific.

Harnessing the cellular and molecular complexity of high-risk neuroblastoma to investigate novel potential treatment approaches

Neuroblastoma (NB) is the most common type of tumor in infants and the third most common cancer in children. Current clinical practices employ a variety of strategies for NB treatment, ranging from standard chemotherapy to immunotherapy. Due to a lack of knowledge about the molecular mechanisms underlying the disease's onset, aggressive phenotype, and therapeutic resistance, these approaches are ineffective in the majority of instances. MYCN amplification is one of the most well-known genetic alterations associated with high risk in NB. The following work is divided into three sections and aims to provide new insights into the biology of NB and hypothetical new treatment strategies. First, we identified RUNX1T1 as a key gene involved in MYCN-driven NB onset in a transgenic mouse model. Our results suggested that that RUNX1T1 may recruit the Co-REST complex on target genes that regulate the differentiation of NB cells and that the interaction with RCOR3 is essential. Second, we provided insights into the role of MYCN in dysregulating the CDK/RB/E2F pathway controlling the G1/S transition of the cell cycle. We found that RB is dispensable in regulating MYCN amplified NB's cell cycle, providing the rationale for using cyclin/CDK complexes inhibitors in NBs carrying MYCN amplification and relatively high levels of RB1 expression. Third, we generated an M13 bacteriophage platform to target GD2-expressing cells in NB. Here, we generated a recombinant M13 phage capable of binding GD2-expressing cells selectively (M13GD2). Our results showed that M13GD2 chemically conjugated with the photosensitizer ECB04 preserves the retargeting capability, inducing cell death even at picomolar concentrations upon light irradiation. These results provided proof of concept for M13 phage employment in targeted photodynamic therapy for NB, an exciting strategy to overcome resistance to classical immunotherapy.

A double chance to investigate populist influence: The Five Star Movement.

In the last decade, new kinds of European populist parties and movements characterized by a left wing, right wing or “eclectic” attitude have succeeded in entering in governments where they could exert a direct populist influence on their coalition partners or, conversely, become victims themselves of the influence of the institutional background. Such a scenario brought this research to formulate two questions: (i) “To what extent did populist parties succeed in influencing their government coalition partners, leading them to adopt populist rhetoric and change their policy positions?” and (ii) “Have populist parties been able to retain their populist “outside mainstream politics” identity, or have they been assimilated to mainstream parties?”. As a case study this project chose the Italian Five Star Movement. Since 2018 this eclectic populist actor has experienced three different governments first with the radical right wing populist League (2018-2019) and then with the mainstream center left Democratic Party (2019-2021). In addition to this, currently the Five Star Movement is a coalition partner of the ongoing Draghi’s government. Theoretically based on the ideological definition of populism (Mudde, 2004), on a new “revised” model of the inclusionary - exclusionary framework to classify populist parties and on a novel definition of “populist influence”,this research made use of both quantitative (bidimensional and text analysis) and qualitative methods (semi-structured interviews) and mainly focuses on the years 2017- 2020.The importance of this study is threefold. First it contributes to the study of populist influence in government in relation to the ideological attachment of the political actors involved. Second, it contributes to understand if populists in power necessarily need to tone down their anti-system character in order to survive. Third, this study introduces conceptual and methodological novelties within the study of populism and populist influence in government.

A 3D biomimetic in vitro model: a novel strategy to investigate glioma biology

Gliomas are one of the most frequent primary malignant brain tumors. Acquisition of stem-like features likely contributes to the malignant nature of high-grade gliomas and may be responsible for the initiation, growth, and recurrence of these tumors. In this regard, although the traditional 2D cell culture system has been widely used in cancer research, it shows limitations in maintaining the stemness properties of cancer and in mimicking the in vivo microenvironment. In order to overcome these limitations, different three-dimensional (3D) culture systems have been developed to mimic better the tumor microenvironment. Cancer cells cultured in 3D structures may represent a more reliable in vitro model due to increased cell-cell and cell-extracellular matrix (ECM) interaction. Several attempts to recreate brain cancer tissue in vitro are described in literature. However, to date, it is still unclear which main characteristics the ideal model should reproduce. The overall goal of this project was the development of a 3D in vitro model able to reproduce the brain ECM microenvironment and to recapitulate pathological condition for the study of tumor stroma interactions, tumor invasion ability, and molecular phenotype of glioma cells. We performed an in silico bioinformatic analysis using GEPIA2 Software to compare the expression level of seven matrix protein in the LGG tumors with healthy tissues. Then, we carried out a FFPE retrospective study in order to evaluate the percentage of expression of selected proteins. Thus, we developed a 3D scaffold composed by Hyaluronic Acid and Collagen IV in a ratio of 50:50. We used two astrocytoma cell lines, HTB-12 and HTB-13. In conclusion, we developed an in vitro 3D model able to reproduce the composition of brain tumor ECM, demonstrating that it is a feasible platform to investigate the interaction between tumor cells and the matrix.

Metabolomics to investigate the effects of treatments on food and of food consumption on health

Metabolomics has established itself as a discipline that can offer a unique point of view on how a technological treatment could impact on the charactersitics of a food. Even more, the same analytical platforms necessary for the purpose can also effectively unravel intricate interactions between such food and human health upon consumption. This PhD thesis investigates the application of metabolomics in understanding the impact of technological treatments on food and their subsequent effects on human health, utilizing 1H-NMR as the analytical platform. The study involves the development of standard operating procedures (SOPs) to ensure a fast and stable preparation of seafood samples, incorporating novel algorithms to enhance the accuracy of metabolome profiles. To gain insight on how metabolomics can allow exploring the effects of a technological treatment on a food, we performed three sets of experiments to investigate the application of metabolomics in studying the impact of high hydrostatic pressure (HHP) treatment on seafood metabolome during storage. The first experiment employs untargeted metabolomic analysis on chill-stored rose shrimp, revealing significant post-HHP treatment metabolic alterations and mechanisms. The investigation is extended to grey mullet in the second experiment, utilizing both untargeted and targeted metabolomic analyses to account for matrix-related effects. The third experiment assesses the targeted metabolome of striped prawns, showing that HHP significantly influences metabolic pathways, positively impacting freshness and taste through alterations in related metabolites. Shifting focus to the effects of food on humans, the study explores the impact of multistrain probiotics on cirrhosis patients using 1H-NMR. The platform reveals notable alterations in glutamine/glutamate metabolism, enhancing the patients' ammonia detoxification capacity. This research underscores the potential of metabolomics in uncovering intricate interactions between technological treatments, food, and human health, providing valuable insights for both the food industry and healthcare interventions.

Deep learning and spatial transcriptomics to investigate thyroid tumors

There are many diseases that affect the thyroid gland, and among them are carcinoma. Thyroid cancer is the most common endocrine neoplasm and the second most frequent cancer in the 0-49 age group. This thesis deals with two studies I conducted during my PhD. The first concerns the development of a Deep Learning model to be able to assist the pathologist in screening of thyroid cytology smears. This tool created in collaboration with Prof. Diciotti, affiliated with the DEI-UNIBO "Guglielmo Marconi" Department of Electrical Energy and Information Engineering, has an important clinical implication in that it allows patients to be stratified between those who should undergo surgery and those who should not. The second concerns the application of spatial transcriptomics on well-differentiated thyroid carcinomas to better understand their invasion mechanisms and thus to better comprehend which genes may be involved in the proliferation of these tumors. This project specifically was made possible through a fruitful collaboration with the Gustave Roussy Institute in Paris. Studying thyroid carcinoma deeply is essential to improve patient care, increase survival rates, and enhance the overall understanding of this prevalent cancer. It can lead to more effective prevention, early detection, and treatment strategies that benefit both patients and the healthcare system.