Quality and safety of oils and fats obtained as co-products or by-products of the food chain and destined to animal production

The aim of the first part of this thesis was to evaluate the effect of trans fatty acid- (TFA), contaminant, polycyclic aromatic hydrocarbon (PAH)- and oxidation productenriched diets on the content of TFA and conjugated linoleic acid (CLA) isomers in meat and liver of both poultry and rabbit. The enriched feedings were prepared with preselected fatty co-and by-products that contained low and high levels of TFA (low, palm fatty acid distillate; high, hydrogenated palm fatty acid distillate), environmental contaminants (dioxins and PCBs) (two different fish oils), PAH (olive oil acid oils and pomace olive oil from chemical refining, for low and high levels) and oxidation products (sunflower-olive oil blend before and after frying), so as to obtain single feedings with three enrichment degrees (high, medium and low) of the compound of interest. This experimental set-up is a part of a large, collaborative European project (http://www.ub.edu/feedfat/), where other chemical and health parameters are assessed. Lipids were extracted, methylated with diazomethane, then transmethylated with 2N KOH/methanol and analyzed by GC and silver-ion TLC-GC. TFA and CLA were determined in the fats, the feedings, meat and liver of both poultry and rabbit. In general, the level of TFA and CLA in meat and liver mainly varied according to those originally found in the feeding fats. It must be pointed out, though, that TFA and CLA accumulation was different for the two animal species, as well as for the two types of tissues. The TFA composition of meat and liver changes according to the composition of the oils added to the feeds with some differences between species. Chicken meat with skin shows higher TFA content (2.6–5.4 fold) than rabbit meat, except for the “PAH” trial. Chicken liver shows higher TFA content (1.2–2.1 fold) than rabbit liver, except for the “TRANS” and “PAH” trials. In both chicken and rabbit meats, the TFA content was higher for the “TRANS” trial, followed by the “DIOXIN” trial. Slight differences were found on the “OXIDATION” and “PAH” trends in both types of meats. In both chicken and rabbit livers, the TFA content was higher for the “TRANS” trial, followed by those of the “PAH”, “DIOXIN” and “OXIDATION” trials. This trend, however, was not identical to that of feeds, where the TFA content varied as follows: “TRANS” > “DIOXIN” >“PAH” > “OXIDATION”. In chicken and rabbit meat samples, C18:1 TFA were the most abundant, followed by C18:2 TFA and C18:3 TFA, except for the “DIOXIN” trial where C18:3 TFA > C18:2 TFA. In chicken and rabbit liver samples of the “TRANS” and “OXIDATION” trials, C18:1 TFA were the most abundant, followed by C18:2 TFA and C18:3 TFA, whereas C18:3 TFA > C18:2 in the “DIOXIN” trial. Slight differences were found on the “PAH” trend in livers from both species. The second part of the thesis dealt with the study of lipid oxidation in washed turkey muscle added with different antioxidants. The evaluation on the oxidative stability of muscle foods found that oxidation could be measured by headspace solid phase microestraction (SPME) of hexanal and propanal. To make this method effective, an antioxidant system was added to stored muscle to stop the oxidative processes. An increase in ionic strength of the sample was also implemented to increase the concentration of aldehydes in the headspace. This method was found to be more sensitive than the commonly used thiobarbituric acid reactive substances (TBARs) method. However, after antioxidants were added and oxidation was stopped, the concentration of aldehydes decreased. It was found that the decrease in aldehyde concentration was due to the binding of the aldehydes to muscle proteins, thus decreasing the volatility and making them less detectable.

Bio-preservation and bio-active compounds as sustainable strategies to improve quality and safety of fresh and fermented products

The development of new “green” and sustainable approaches to reduce food wastes, guaranteeing food quality, microbiological safety and the environmental sustainability, is of great interest for food industry. This PhD thesis, as part of the European project BioProMedFood (PRIMA–Section2 Programme), was focused on two strategies: the use of natural antimicrobials and the application of microbial strains isolated from spontaneously fermented products. The first part concerned the valorisation of microbial biodiversity of 15 Mediterranean spontaneously fermented sausages, through the isolation of autochthonous lactic acid bacteria (LAB) strains, mainly Latilactobacillus sakei, that were characterised regarding their safety and technological aspects. The most promising strains were tested as bio-protective cultures in fresh sausages, showing promising anti-listerial activity, or as starter cultures in fermented sausages. The second part of the research was focused on the use of natural compounds (phenolic extracts and essential oils from Juniperus oxycedrus needles and Rubus fruticosus leaves) with antimicrobial potential. They were tested in vitro against List. monocytogenes and Enterococcus faecium, showing differences in relation to species and type of extracts, but they hint at important possibilities for applications in specific foods. Concluding, this PhD thesis highlighted the great potential of traditional meat products as an isolation source of new strains with industrial importance. Moreover, the antimicrobial potential of compounds obtained from plant matrices opened promising perspectives to exploit them as “green” strategies to increase fresh food safety. The last topic of research, carry out in collaboration with Department of Nutrition and Food Sciences (University of Granada), investigated the effect of LAB fermentation on avocado leaves by-products, focusing on the bio-availability of phenolic compounds in the plant extracts, caused by microbial metabolism.

A regional environmental accounting matrix and integrated environmental economic analyses to support regional planning

This research deals with the deepening and use of an environmental accounting matrix in Emilia-Romagna, RAMEA air emissions (regional NAMEA), carried out by the Regional Environment Agency (Arpa) in an European project. After a depiction of the international context regarding the widespread needing to integrate economic indicators and go beyond conventional reporting system, this study explains the structure, update and development of the tool. The overall aim is to outline the matrix for environmental assessments of regional plans, draw up sustainable reports and monitor effects of regional policies in a sustainable development perspective. The work focused on an application of a Shift-Share model, on the integration with eco-taxes, industrial waste production, energy consumptions, on applications of the extended RAMEA as a policy tool, following Eurostat guidelines. The common thread is the eco-efficiency (economic-environmental efficiency) index. The first part, in English, treats the methodology used to build a more complete tool; in the second part RAMEA has been applied on two regional case studies, in Italian, to support decision makers regarding Strategic Environmental Assessments’ processes (2001/42/EC). The aim is to support an evidence-based policy making by integrating sustainable development concerns at all levels. The first case study regards integrated environmental-economic analyses in support to the SEA of the Regional Waste management plan. For the industrial waste production an extended and updated RAMEA has been developed as a useful policy tool, to help in analysing and monitoring the state of environmental-economic performances. The second case study deals with the environmental report for the SEA of the Regional Program concerning productive activities. RAMEA has been applied aiming to an integrated environmental-economic analysis of the context, to investigate the performances of the regional production chains and to depict and monitor the area where the program should be carried out, from an integrated environmental-economic perspective.

Predictive And Prognostic Role Of Biological Markers In Neuroendocrine Neoplasia And Evaluation Of Activity And Safety Of Second Line Treatments In Neuroendocrine Carcinoma Patients

BACKGROUND Neuroendocrine neoplasia (NEN) are divided in well differentiated G1,G2 and G3 neuroendocrine tumors (NETs) and G3 neuroendocrine carcinomas (NECs). For the latter no standard therapy in second-line is available and prognosis is poor. METHODS Primary aim was to evaluate new prognostic and predictive biomarkers (WP1-3). In WP4 we explored the activity of FOLFIRI and CAPTEM as second-line in NEC patients in a multicenter non-comparative phase II trial RESULTS In WP1-2 we found that 4 of 6 GEP-NEC patients with a negative 68Ga-PET/CT had a loss of expression of RB1. In WP3 on 47 GEP-NENs patients the presence of DLL3 in 76.9% of G3 NEC correlate with RB1-loss (p<0.001), negative 68Ga-PET/CT(p=0.001) and a poor prognosis. In the WP4 we conducted a multicenter non-comparative phase II trial to explore the activity of FOLFIRI or CAPTEM in terms of DCR, PFS and OS given as second-line in NEC patients. From 06/03/2017 to 18/01/2021 53 out of 112 patients were enrolled in 17 of 23 participating centers. Median follow-up was 10.8 (range 1.4 – 38.6) months. The 3-month DCR was 39.3% in the FOLFIRI and 32.0 % in the CAPTEM arm. The 6-months PFS rate was 34.6% ( 95%CI 17.5-52.5) in FOLFIRI and 9.6% (95%CI 1.8-25.7) in CAPTEM group. In the FOLFIRI subgroup the 6-months and 12-months OS rate were 55.4% (95%CI 32.6-73.3) and 30.3% (CI 11.1-52.2) respectively. In CAPTEM arm the 6-months and 12-months OS rate were 57.2% (95%34.9-74.3) and 29.0% (95%10.0-43.3). The miRNA analysis of 20 patients compared with 20 healthy subjects shows an overexpression of miRNAs involved in staminality , neo-angiogenesis and mitochontrial anaerobic glycolysis activation. CONCLUSION WP1-3 support the hypothesis that G3NECs carrying RB1 loss is associated with a DLL3 expression highlighting a potential therapeutic opportunity. Our study unfortunately didn’t met the primary end–point but the results are promising

Towards cheaper, safer and low environmental impact materials for energy storage devices: natural resources-derived carbon based electrodes and aqueous electrolytes for supercapacitors

The growing market of electrical cars, portable electronics, photovoltaic systems..etc. requires the development of efficient, low-cost, and low environmental impact energy storage devices (ESDs) including batteries and supercapacitors.. Due to their extended charge-discharge cycle, high specific capacitance, and power capabilities supercapacitors are considered among the most attractive ESDs. Over the last decade, research and development in supercapacitor technology have accelerated: thousands of articles have been published in the literature describing the electrochemical properties of the electrode materials and electrolyte in addition to separators and current collectors. Carbon-based supercapacitor electrodes materials have gained increasing attention due to their high specific surface area, good electrical conductivity, and excellent stability in harsh environments, as well as other characteristics. Recently, there has been a surge of interest in activated carbon derived from low-cost abundant sources such as biomass for supercapacitor electrode materials. Also, particular attention was given to a major challenging issue concerning the substitution of organic solutions currently used as electrolytes due to their highest electrochemical stability window even though their high cost, toxicity, and flammability. In this regard, the main objective of this thesis is to investigate the performances of supercapacitors using low cost abundant safe, and low environmental impact materials for electrodes and electrolytes. Several prototypes were constructed and tested using natural resources through optimization of the preparation of appropriate carbon electrodes using agriculture by-products waste or coal (i.e. Argan shell or Anthracite from Jerrada). Such electrodes were tested using several electrolyte formulations (aqueous and water in salt electrolytes) beneficing their non-flammability, lower cost, and environmental impact; the characteristics that provide a promising opportunity to design safer, inexpensive, and environmentally friendly devices compared to organic electrolytes.

Analysis of efficacy and safety of CAR T-cell therapy in relapsed/refractory lymphomas: current indications and future perspectives

In the last few years, the introduction of chimeric antigen receptor (CAR) T-cell therapy into clinical practice has revolutionized the approach to patients with relapsed/refractory (R/R) large B-cell lymphoma (LBCL), whose outcome used to be dismal with median overall survival (OS) of approximately 6 months with standard salvage therapy. At our Institute, we started treating diffuse large B-cell lymphoma (DLBCL) patients with CAR T-cell products in August 2019 and they received either axicabtagene ciloleucel (axi-cel) and tisagenlecleucel (tisa-cel) as per regulatory indications. This research project presents the 2-year follow-up of the first 53 treated patients. Our first aim is to investigate the feasibility of this treatment strategy in a real-world setting, although the reimbursement criteria set by the Italian Medicines Agency (Agenzia Italiana del Farmaco, AIFA) are very similar to the inclusion criteria of clinical trials and stricter than those established by the regulatory authorities of many foreign countries. One month after infusion, the ORR was 66% with 19 patients already in CR (38%). Restaging at 3, 6 and 12 months post-infusion shows that early CRs tend to be maintained over time and, moreover, that a considerable number of PRs and a few SDs can improve into a CR. The safety data were consistent with what is reported in the literature; toxicity was generally manageable, largely due to the increasing expertise in handling the specific adverse events related to CAR T-cell therapy. Our results confirms that CAR T-cell therapy is both safe and effective in a real-life setting and that it represents a crucial weapon in a subset of patients who were previously doomed to an inevitably severe prognosis.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.