Cell-free cryopreserved arterial allografts from multiorgan donors: a new strategy to fabricate artificial blood vessels suited for peripheral vascular surgery

Critical lower limb ischemia is a severe disease. A common approach is infrainguinal bypass. Synthetic vascular prosthesis, are good conduits in high-flow low-resistance conditions but have difficulty in their performance as small diameter vessel grafts. A new approach is the use of native decellularized vascular tissues. Cell-free vessels are expected to have improved biocompatibility when compared to synthetic and are optimal natural 3D matrix templates for driving stem cell growth and tissue assembly in vivo. Decellularization of tissues represent a promising field for regenerative medicine, with the aim to develop a methodology to obtain small-diameter allografts to be used as a natural scaffold suited for in vivo cell growth and pseudo-tissue assembly, eliminating failure caused from immune response activation. Material and methods. Umbilical cord-derived mesenchymal cells isolated from human umbilical cord tissue were expanded in advanced DMEM. Immunofluorescence and molecular characterization revealed a stem cell profile. A non-enzymatic protocol, that associate hypotonic shock and low-concentration ionic detergent, was used to decellularize vessel segments. Cells were seeded cell-free scaffolds using a compound of fibrin and thrombin and incubated in DMEM, after 4 days of static culture they were placed for 2 weeks in a flow-bioreactor, mimicking the cardiovascular pulsatile flow. After dynamic culture, samples were processed for histological, biochemical and ultrastructural analysis. Discussion. Histology showed that the dynamic culture cells initiate to penetrate the extracellular matrix scaffold and to produce components of the ECM, as collagen fibres. Sirius Red staining showed layers of immature collagen type III and ultrastructural analysis revealed 30 nm thick collagen fibres, presumably corresponding to the immature collagen. These data confirm the ability of cord-derived cells to adhere and penetrate a natural decellularized tissue and to start to assembly into new tissue. This achievement makes natural 3D matrix templates prospectively valuable candidates for clinical bypass procedures

Development of synthetic molecular circuits for the control of cell systems

Synthetic biology is a young field of applicative research aiming to design and build up artificial biological devices, useful for human applications. How synthetic biology emerged in past years and how the development of the Registry of Standard Biological Parts aimed to introduce one practical starting solution to apply the basics of engineering to molecular biology is presented in chapter 1 in the thesis The same chapter recalls how biological parts can make up a genetic program, the molecular cloning tecnique useful for this purpose, and an overview of the mathematical modeling adopted to describe gene circuit behavior. Although the design of gene circuits has become feasible the increasing complexity of gene networks asks for a rational approach to design gene circuits. A bottom-up approach was proposed, suggesting that the behavior of a complicated system can be predicted from the features of its parts. The option to use modular parts in large-scale networks will be facilitated by a detailed and shared characterization of their functional properties. Such a prediction, requires well-characterized mathematical models of the parts and of how they behave when assembled together. In chapter 2, the feasibility of the bottom-up approach in the design of a synthetic program in Escherichia coli bacterial cells is described. The rational design of gene networks is however far from being established. The synthetic biology approach can used the mathematical formalism to identify biological information not assessable with experimental measurements. In this context, chapter 3 describes the design of a synthetic sensor for identifying molecules of interest inside eukaryotic cells. The Registry of Standard parts collects standard and modular biological parts. To spread the use of BioBricks the iGEM competition was started. The ICM Laboratory, where Francesca Ceroni completed her Ph.D, partecipated with teams of students and Chapter 4 summarizes the projects developed.

Patterning soft matter for cell culturing

In the search to understand the interaction between cells and their underlying substrates, life sciences are beginning to incorporate micro and nano-technology based tools to probe, measure and improve cellular behavior. In this frame, patterned surfaces provide a platform for highly defined cellular interactions and, in perspective, they offer unique advantages for artificial implants. For these reasons, functionalized materials have recently become a central topic in tissue engineering. Nanotechnology, with its rich toolbox of techniques, can be the leading actor in the materials patterning field. Laser assisted methods, conventional and un-conventional lithography and other patterning techniques, allow the fabrication of functional supports with tunable properties, either physically, or topographically and chemically. Among them, soft lithography provides an effective (and low cost) strategy for manufacturing micro and nanostructures. The main focus of this work is the use of different fabrication approaches aiming at a precise control of cell behavior, adhesion, proliferation and differentiation, through chemically and spatially designed surfaces.

Organic photosensitizers and nanostructured semiconductors for photoredox catalysis and artificial photosynthesis

Over the course of evolution, Nature has elegantly learned to use light to drive chemical reactions. On the other hand, humans have only recently started learning how to play with this powerful tool to carry out chemical transformations. In particular, a step forward was possible thanks to molecules and materials that can absorb light and trigger a series of processes that can drive chemical reactions. However, scarce elements are extensively employed in the design of most of these compounds and considerations on their scarcity and toxicity have sparked interest on alternatives based on earth-abundant elements. In this framework, the focus of this thesis has been the development and employment of heavy-metal free chromophores and of earth-abundant oxides. The first chapter regards the functionalization of boron-dipyrromethenes (BODIPYs) so as to allow access to their triplet excited state and tune their redox potentials, which was achieved thanks to the design of orthogonal donor-acceptor dyads. The BODIPY dyads were used to promote a photoredox reaction, and the mechanism of the reaction was clarified. In the second chapter, organic chromophores that display thermally-activated delayed fluorescence (TADF) were studied. These were used to perform enantioselective photoredox reactions, and a mechanistic investigation allowed to elucidate the fate of these photosensitizers in the reaction. Thanks to their stronger reducing power, it was possible to demonstrate the employability of TADF dyes in artificial photosynthesis, as well. Last, the oxidation of biomass-derived compounds was studied in a photoelectrochemical cell. For this purpose, hematite photoanodes were synthesized in collaboration with Prof. Caramori’s group at the University of Ferrara (Italy) and they were tested in the presence of a redox mediator. In addition to this, the possibility of repurposing a copper(II) water oxidation catalyst for the oxidation of biomass was investigated in collaboration with Prof. Llobet’s group at ICIQ (Tarragona, Spain).

Anticancer drug discovery using artificial intelligence: an application in pharmacological activity prediction

Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.