Liquidity, business cycles and monetary policy: A simulation

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Development and application of NMR techniques to study water-in-CO2 microemulsions

Self-assembly is a phenomenon that occurs frequently throughout the universe. In this work, two self-assembling systems were studied: the formation of reverse micelles in isooctane and in supercritical CO2 (scCO2), and the formation of gels in organic solvents. The goal was the physicochemical study of these systems and the development of an NMR methodology to study them. In this work, AOT was used as a model molecule both to comprehensively study a widely researched system water/AOT/isooctane at different water concentrations and to assess its aggregation in supercritical carbon dioxide at different pressures. In order to do so an NMR methodology was devised, in which it was possible to accurately determine hydrodynamic radius of the micelle (in agreement with DLS measurements) using diffusion ordered spectroscopy (DOSY), the micellar stability and its dynamics. This was mostly assessed by 1H NMR relaxation studies, which allowed to determine correlation times and size of correlating water molecules, which are in agreement with the size of the shell that interacts with the micellar layer. The encapsulation of differently-sized carbohydrates was also studied and allowed to understand the dynamics and stability of the aggregates in such conditions. A W/CO2 microemulsion was prepared using AOT and water in scCO2, with ethanol as cosurfactant. The behaviour of the components of the system at different pressures was assessed and it is likely that above 130 bar reverse microemulsions were achieved. The homogeneity of the system was also determined by NMR. The formation of the gel network by two small molecular organogelators in toluene-d8 was studied by DOSY. A methodology using One-shot DOSY to perform the spectra was designed and applied with success. This yielded an understanding about the role of the solvent and gelator in the aggregation process, as an estimation of the time of gelation.

Improving accuracy of inflation forecasts using macroeconomic information

This thesis examines the effects of macroeconomic factors on inflation level and volatility in the Euro Area to improve the accuracy of inflation forecasts with econometric modelling. Inflation aggregates for the EU as well as inflation levels of selected countries are analysed, and the difference between these inflation estimates and forecasts are documented. The research proposes alternative models depending on the focus and the scope of inflation forecasts. I find that models with a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) in mean process have better explanatory power for inflation variance compared to the regular GARCH models. The significant coefficients are different in EU countries in comparison to the aggregate EU-wide forecast of inflation. The presence of more pronounced GARCH components in certain countries with more stressed economies indicates that inflation volatility in these countries are likely to occur as a result of the stressed economy. In addition, other economies in the Euro Area are found to exhibit a relatively stable variance of inflation over time. Therefore, when analysing EU inflation one have to take into consideration the large differences on country level and focus on those one by one.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.