Social Welfare and Behavioral Public Policies

In this work I discuss several key aspects of welfare economics and policy analysis and I propose two original contributions to the growing field of behavioral public policymaking. After providing a historical perspective of welfare economics and an overview of policy analysis processes in the introductory chapter, in chapter 2 I discuss a debated issue of policymaking, the choice of the social welfare function. I contribute to this debate by proposing an original methodological contribution based on the analysis of the quantitative relationship among different social welfare functional forms commonly used by policy analysts. In chapter 3 I then discuss a behavioral policy to contrast indirect tax evasion based on the use of lotteries. I show that the predictions of my model based on non-expected utility are consistent with observed, and so far unexplained, empirical evidence of the policy success. Finally, in chapter 4 I investigate by mean of a laboratory experiment the effects of social influence on the individual likelihood to engage in altruistic punishment. I show that bystanders’ decision to engage in punishment is influenced by the punishment behavior of their peers and I suggest ways to enact behavioral policies that exploit this finding.

A take on complexity: bio-molecules and human metabolism interaction modelling for health and nutrition with machine learning

The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.

Methods and tools to foster territorial approaches for the assessment of food supply chains

The challenges of the current global food systems are often framed around feeding the world's growing population while meeting sustainable development for future generations. Globalization has brought to a fragmentation of food spaces, leading to a flexible and mutable supply chain. This poses a major challenge to food and nutrition security, affecting also rural-urban dynamics in territories. Furthermore, the recent crises have highlighted the vulnerability to shocks and disruptions of the food systems and the eco-system due to the intensive management of natural, human and economic capital. Hence, a sustainable and resilient transition of the food systems is required through a multi-faceted approach that tackles the causes of unsustainability and promotes sustainable practices at all levels of the food system. In this respect, a territorial approach becomes a relevant entry point of analysis for the food system’s multifunctionality and can support the evaluation of sustainability by quantifying impacts associated with quantitative methods and understanding the territorial responsibility of different actors with qualitative ones. Against this background the present research aims to i) investigate the environmental, costing and social indicators suitable for a scoring system able to measure the integrated sustainability performance of food initiatives within the City/Region territorial context; ii) develop a territorial assessment framework to measure sustainability impacts of agricultural systems; and iii) define an integrated methodology to match production and consumption at a territorial level to foster a long-term vision of short food supply chains. From a methodological perspective, the research proposes a mixed quantitative and qualitative research method. The outcomes provide an in-depth view into the environmental and socio-economic impacts of food systems at the territorial level, investigating possible indicators, frameworks, and business strategies to foster their future sustainable development.

Development of new therapeutic approaches in the treatments of Inflammatory Bowel Diseases: functional food and nutraceuticals vs synthetic peptides based vaccines

Inflammatory Bowel Diseases (IBD) are intestinal chronic relapsing diseases which ethiopathogenesis remains uncertain. Several group have attempted to study the role of factors involved such as genetic susceptibility, environmental factors such as smoke, diet, sex, immunological factors as well as the microbioma. None of the treatments available satisfy several criteria at the same time such as safety, long-term remission, histopatological healing, and specificity. We used two different approaches for the development of new therapeutic treatment for Inflammatory Bowel Disease. The first is focused on the understanding of the potential role of functional food and nutraceuticals nutrients in the treatment of IBD. To do so, we investigated the role of Curcuma longa in the treatment of chemical induced colitis in mice model. Since Curcma Longa has been investigated for its antinflammatory role related to the TNFα pathway as well investigators have reported few cases of patients with ulcerative colites treated with this herbs, we harbored the hypothesis of a role of Curcuma Longa in the treatment f IBD as well as we decided to assess its role in intestinal motility. The second part is based on an immunological approach to develop new drugs to induce suppression in Crohn’s disease or to induce mucosa immunity such as in colonrectal tumor. The main idea behind this approach is that we could manipulate relevant cell-cell interactions using synthetic peptides. We demonstrated the role of the unique interaction between molecules expressed on intestinal epithelial cells such as CD1d and CEACAM5 and on CD8+ T cells. In normal condition this interaction has a role for the expansion of the suppressor CD8+ T cells. Here, we characterized this interaction, we defined which are the epitope involved in the binding and we attempted to develop synthetic peptides from the N domain of CEACAM5 in order to manipulate it.

Phenotypic and genotypic characterisation of antimicrobial resistance in Escherichia coli indicator of animal, food and human origin.

This thesis presents AMR phenotypic evaluation and whole genome sequencing analysis of 288 Escherichia coli strains isolated from different sources (livestock, companion animal, wildlife, food and human) in Italy. Our data reflects general resistance trends in Europe, reporting tetracycline, ampicillin, sulfisoxazole and aminoglycosides resistance as the most common phenotypic AMR profile among livestock, pets, wildlife and humans. Identification of human and animal (livestock and companion animal) AMR profiles in niches with a rare (fishery, mollusc) or absent (vegetable, wild animal, wild boar) direct exposure to antimicrobials, suggests widespread environmental pollution with ARGs conferring resistance to these antimicrobials. Phenotypic resistance to highest priority critically important antimicrobials was mainly observed in food-producing animals and related food such as rabbit, poultry, beef and swine. Discrepancies between AMR phenotypic pattern and genetic profile were observed. In particular, phenotypic aminoglycoside, cephalosporin, meropenem, colistin resistance and ESBL profile did not have a genetic explanation in different cases. This data could suggest the diffusion of new genetic variants of ARGs, associated to these antimicrobial classes. Generally, our collection shows a virulence profile typical of extraintestinal pathogenic Escherichia coli (ExPEC) pathotype. Different pandemic and emerging ExPEC lineages were identified, in particular in poultry meat (ST10; ST23; ST69, ST117; ST131). Rabbit was suggested as a source of ST20-ST40 potential hybrid pathogens. Wildlife carried a high average number (10) of VAGs (mostly associated to ExPEC pathotype) and different predominant ExPEC lineages (ST23, ST117, ST648), suggesting its possible involvement in maintenance and diffusion of virulence determinants. In conclusion, our study provides important knowledge related to the phenotypic/genetic AMR and virulence profiles circulating in E. coli in Italy. The role of different niches in AMR dynamics has been discussed. In particular, food-producing animals are worthy of continued investigation as a source of potential zoonotic pathogens, meanwhile wildlife might contribute to VAGs spread.

Dynamic food systems and climate-induced risks transmission for food and nutritional security

Agriculture market instability impedes achieving the global goal of sustainable and resilient food systems. Currently, the support to producers reaches the mammoth USD 540 billion a year and is projected to reach USD 1.8 trillion by 2030. This gigantic increase requires a repurposing agricultural support strategy (RASS), considering the market country-specific circumstances. These circumstances may vary with geographic locations, marketing structures, and product value chains. The fruit production system is crucial for health-conscious consumers and profit-oriented producers for food and nutritional security. Export is one of the main driving forces behind the expansion of the fruit sector, and during the year 2010-2018, trade significantly outpaced production increases. The previous literature states that irregular and unpredictable behaviour — Chaos — can arise from entirely rational economic decision-making within markets. Different markets' direct/indirect linkages through trade create trade hubs, and uncertainty may function as an avenue to transmit adverse shocks and increase vulnerability rather than contribute to resilience. Therefore, distinguishing Chaos into an endogenous and exogenous pattern of behaviour is cradled to formulate an effective RASS for resilient food systems and to understand global food crises. The present research is aimed at studying the market dynamics of three regional trade hubs, i.e., Brazil (South America), Italy (Europe), and Pakistan (Asia), each representing advanced to traditional value chains to control uncertainty (risks). The present research encompasses 1) a systematic review to highlight the research dynamism and identify grey-areas of research. Based on the findings, we have investigated the 2) nonlinear impacts of climate-induced price responsiveness in monopsony markets. Once we highlighted the importance of marketing structures/arrangements, 3) we developed a risk transmission framework to address the co-evolving impacts in complex dynamic interactions.

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.