Porous Polymeric Bioresorbable Scaffolds for Tissue Engineering

Tissue engineering is a discipline that aims at regenerating damaged biological tissues by using a cell-construct engineered in vitro made of cells grown into a porous 3D scaffold. The role of the scaffold is to guide cell growth and differentiation by acting as a bioresorbable temporary substrate that will be eventually replaced by new tissue produced by cells. As a matter or fact, the obtainment of a successful engineered tissue requires a multidisciplinary approach that must integrate the basic principles of biology, engineering and material science. The present Ph.D. thesis aimed at developing and characterizing innovative polymeric bioresorbable scaffolds made of hydrolysable polyesters. The potentialities of both commercial polyesters (i.e. poly-e-caprolactone, polylactide and some lactide copolymers) and of non-commercial polyesters (i.e. poly-w-pentadecalactone and some of its copolymers) were explored and discussed. Two techniques were employed to fabricate scaffolds: supercritical carbon dioxide (scCO2) foaming and electrospinning (ES). The former is a powerful technology that enables to produce 3D microporous foams by avoiding the use of solvents that can be toxic to mammalian cells. The scCO2 process, which is commonly applied to amorphous polymers, was successfully modified to foam a highly crystalline poly(w-pentadecalactone-co-e-caprolactone) copolymer and the effect of process parameters on scaffold morphology and thermo-mechanical properties was investigated. In the course of the present research activity, sub-micrometric fibrous non-woven meshes were produced using ES technology. Electrospun materials are considered highly promising scaffolds because they resemble the 3D organization of native extra cellular matrix. A careful control of process parameters allowed to fabricate defect-free fibres with diameters ranging from hundreds of nanometers to several microns, having either smooth or porous surface. Moreover, versatility of ES technology enabled to produce electrospun scaffolds from different polyesters as well as “composite” non-woven meshes by concomitantly electrospinning different fibres in terms of both fibre morphology and polymer material. The 3D-architecture of the electrospun scaffolds fabricated in this research was controlled in terms of mutual fibre orientation by properly modifying the instrumental apparatus. This aspect is particularly interesting since the micro/nano-architecture of the scaffold is known to affect cell behaviour. Since last generation scaffolds are expected to induce specific cell response, the present research activity also explored the possibility to produce electrospun scaffolds bioactive towards cells. Bio-functionalized substrates were obtained by loading polymer fibres with growth factors (i.e. biomolecules that elicit specific cell behaviour) and it was demonstrated that, despite the high voltages applied during electrospinning, the growth factor retains its biological activity once released from the fibres upon contact with cell culture medium. A second fuctionalization approach aiming, at a final stage, at controlling cell adhesion on electrospun scaffolds, consisted in covering fibre surface with highly hydrophilic polymer brushes of glycerol monomethacrylate synthesized by Atom Transfer Radical Polymerization. Future investigations are going to exploit the hydroxyl groups of the polymer brushes for functionalizing the fibre surface with desired biomolecules. Electrospun scaffolds were employed in cell culture experiments performed in collaboration with biochemical laboratories aimed at evaluating the biocompatibility of new electrospun polymers and at investigating the effect of fibre orientation on cell behaviour. Moreover, at a preliminary stage, electrospun scaffolds were also cultured with tumour mammalian cells for developing in vitro tumour models aimed at better understanding the role of natural ECM on tumour malignity in vivo.

3D nanostructured microcarriers for cell therapy in regenerative medicine

Supercritical Emulsion Extraction technology (SEE-C) was proposed for the production of poly-lactic-co-glycolic acid microcarriers. SEE-C operating parameters as pressure, temperature and flow rate ratios were analyzed and the process performance was optimized in terms of size distribution and encapsulation efficiency. Microdevices loaded with bovine serum insulin were produced with different sizes (2 and 3 µm) or insulin charges (3 and 6 mg/g) and with an encapsulation efficiency of 60%. The microcarriers were characterized in terms of insulin release profile in two different media (PBS and DMEM) and the diffusion and degradation constants were also estimated by using a mathematical model. PLGA microdevices were also used in a cultivation of embryonic ventricular myoblasts (cell line H9c2 obtained from rat) in a FBS serum free medium to monitor cell viability and growth in dependence of insulin released. Good cell viability and growth were observed on 3 µm microdevices loaded with 3 mg/g of insulin. PLGA microspheres loaded with growth factors (GFs) were charged into alginate scaffold with human Mesenchimal Steam Cells (hMSC) for bone tissue engineering with the aim of monitoring the effect of the local release of these signals on cells differentiation. These “living” 3D scaffolds were incubated in a direct perfusion tubular bioreactor to enhance nutrient transport and exposing the cells to a given shear stress. Different GFs such as, h-VEGF, h-BMP2 and a mix of two (ratio 1:1) were loaded and alginate beads were recovered from dynamic (tubular perfusion system bioreactor) and static culture at different time points (1st, 7th, 21st days) for the analytical assays such as, live/dead; alkaline phosphatase; osteocalcin; osteopontin and Van Kossa Immunoassay. The immunoassay confirmed always a better cells differentiation in the bioreactor with respect to the static culture and revealed a great influence of the BMP-2 released in the scaffold on cell differentiation.

Toward a 3D in vitro model based on decellularized thymus to maintain adult thymic ephitelial cells functionality

During my PhD,I have been develop an innovative technique to reproduce in vitro the 3D thymic microenvironment, to be used for growth and differentiation of thymocytes, and possible transplantation replacement in conditions of depressed thymic immune regulation. The work has been developed in the laboratory of Tissue Engineering at the University Hospital in Basel, Switzerland, under the tutorship of Prof.Ivan Martin. Since a number of studies have suggested that the 3D structure of the thymic microenvironment might play a key role in regulating the survival and functional competence of thymocytes, I’ve focused my effort on the isolation and purification of the extracellular matrix of the mouse thymus. Specifically, based on the assumption that TEC can favour the differentiation of pre-T lymphocytes, I’ve developed a specific decellularization protocol to obtain the intact, DNA-free extracellular matrix of the adult mouse thymus. Two different protocols satisfied the main characteristics of a decellularized matrix, according to qualitative and quantitative assays. In particular, the quantity of DNA was less than 10% in absolute value, no positive staining for cells was found and the 3D structure and composition of the ECM were maintained. In addition, I was able to prove that the decellularized matrixes were not cytotoxic for the cells themselves, and were able to increase expression of MHC II antigens compared to control cells grown in standard conditions. I was able to prove that TECs grow and proliferate up to ten days on top the decellularized matrix. After a complete characterization of the culture system, these innovative natural scaffolds could be used to improve the standard culture conditions of TEC, to study in vitro the action of different factors on their differentiation genes, and to test the ability of TECs to induce in vitro maturation of seeded T lymphocytes.

Biomimetic Scaffolds for the Controlled Release of Bioactive Molecules for Tissue Engineering Applications

The temporospatial controlled delivery of growth factors is crucial to trigger the desired healing mechanisms in target tissues. The uncontrolled release of growth factors has been demonstrated to cause severe side effects in its surrounding tissues. Thus, the first working hypothesis was to tune and optimize a newly developed multiscale delivery platform based on a nanostructured silicon particle core (pSi) and a poly (dl-lactide-co-glycolide) acid (PLGA) outer shell. In a murine subcutaneous model, the platform was demonstrated to be fully tunable for the temporal and spatial control release of the payload. Secondly, a multiscale approach was followed in a multicompartment collagen scaffold, to selectively integrate different sets of PLGA-pSi loaded with different reporter proteins. The spatial confinement of the microspheres allowed the release of the reporter proteins in each of the layers of the scaffold. Finally, the staged and zero-order release kinetics enabled the temporal biochemical patterning of the scaffold. The last step of this PhD project was to test if by fully embedding PLGA microspheres in a highly structured and fibrous collagen-based scaffold (camouflaging), it was possible to prevent their early detection and clearance by macrophages. It was further studied whether such a camouflaging strategy was efficient in reducing the production of key inflammatory molecules, while preserving the release kinetics of the payload of the PLGA microspheres. Results demonstrated that the camouflaging allowed for a 10-fold decrease in the number of PLGA microspheres internalized by macrophages, suggesting that the 3D scaffold operated by cloaking the PLGA microspheres. When the production of key inflammatory cytokines induced by the scaffold was assessed, macrophages' response to the PLGA microspheres-integrated scaffolds resulted in a response similar to that observed in the control (not functionalized scaffold) and the release kinetic of a reporter protein was preserved.

Safety by design: production of engineering surface modified nanomaterials

This PhD thesis focused on nanomaterial (NM) engineering for occupational health and safety, in the frame of the EU project “Safe Nano Worker Exposure Scenarios (SANOWORK)”. Following a safety by design approach, surface engineering (surface coating, purification process, colloidal force control, wet milling, film coating deposition and granulation) were proposed as risk remediation strategies (RRS) to decrease toxicity and emission potential of NMs within real processing lines. In the first case investigated, the PlasmaChem ZrO2 manufacturing, the colloidal force control applied to the washing of synthesis rector, allowed to reduce ZrO2 contamination in wastewater, performing an efficient recycling procedure of ZrO2 recovered. Furthermore, ZrO2 NM was investigated in the ceramic process owned by CNR-ISTEC and GEA-Niro; the spray drying and freeze drying techniques were employed decreasing NM emissivity, but maintaining a reactive surface in dried NM. Considering the handling operation of nanofibers (NFs) obtained through Elmarco electrospinning procedure, the film coating deposition was applied on polyamide non-woven to avoid free fiber release. For TiO2 NF the wet milling was applied to reduce and homogenize the aspect ratio, leading to a significant mitigation of fiber toxicity. In the Colorobbia spray coating line, Ag and TiO2 nanosols, employed to transfer respectively antibacterial or depolluting properties to different substrates, were investigated. Ag was subjected to surface coating and purification, decreasing NM toxicity. TiO2 was modified by surface coating, spray drying and blending with colloidal SiO2, improving its technological performance. In the extrusion of polymeric matrix charged with carbon nanotube (CNTs) owned by Leitat, the CNTs used as filler were granulated by spray drying and freeze spray drying techniques, allowing to reduce their exposure potential. Engineered NMs tested by biologists were further investigated in relevant biological conditions, to improve the knowledge of structure/toxicity mechanisms and obtain new insights for the design of safest NMs.

Evaluation of 3D cell culture systems for host-pathogen interaction studies

Traditional cell culture models have limitations in extrapolating functional mechanisms that underlie strategies of microbial virulence. Indeed during the infection the pathogens adapt to different tissue-specific environmental factors. The development of in vitro models resembling human tissue physiology might allow the replacement of inaccurate or aberrant animal models. Three-dimensional (3D) cell culture systems are more reliable and more predictive models that can be used for the meaningful dissection of host–pathogen interactions. The lung and gut mucosae often represent the first site of exposure to pathogens and provide a physical barrier against their entry. Within this context, the tracheobronchial and small intestine tract were modelled by tissue engineering approach. The main work was focused on the development and the extensive characterization of a human organotypic airway model, based on a mechanically supported co-culture of normal primary cells. The regained morphological features, the retrieved environmental factors and the presence of specific epithelial subsets resembled the native tissue organization. In addition, the respiratory model enabled the modular insertion of interesting cell types, such as innate immune cells or multipotent stromal cells, showing a functional ability to release pertinent cytokines differentially. Furthermore this model responded imitating known events occurring during the infection by Non-typeable H. influenzae. Epithelial organoid models, mimicking the small intestine tract, were used for a different explorative analysis of tissue-toxicity. Further experiments led to detection of a cell population targeted by C. difficile Toxin A and suggested a role in the impairment of the epithelial homeostasis by the bacterial virulence machinery. The described cell-centered strategy can afford critical insights in the evaluation of the host defence and pathogenic mechanisms. The application of these two models may provide an informing step that more coherently defines relevant molecular interactions happening during the infection.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.

Understanding 3D structures from sketches

Sketches are a unique way to communicate: drawing a simple sketch does not require any training, sketches convey information that is hard to describe with words, they are powerful enough to represent almost any concept, and nowadays, it is possible to draw directly from mobile devices. Motivated from the unique characteristics of sketches and fascinated by the human ability to imagine 3D objects from drawings, this thesis focuses on automatically associating geometric information to sketches. The main research directions of the thesis can be summarized as obtaining geometric information from freehand scene sketches to improve 2D sketch-based tasks and investigating Vision-Language models to overcome 3D sketch-based tasks limitations. The first part of the thesis concerns geometric information prediction from scene sketches improving scene sketch to image generation and unlocking new creativity effects. The thesis proceeds showing a study conducted on the Vision-Language models embedding space considering sketches, line renderings and RGB renderings of 3D shape to overcome the use of supervised datasets for 3D sketch-based tasks, that are limited and hard to acquire. Following the obtained observations and results, Vision-Language models are applied to Sketch Based Shape Retrieval without the need of training on supervised datasets. We then analyze the use of Vision-Language models for sketch based 3D reconstruction in an unsupervised manner. In the final chapter we report the results obtained in an additional project carried during the PhD, which has lead to the development of a framework to learn an embedding space of neural networks that can be navigated to get ready-to-use models with desired characteristics.