The glial cell-line derived neurotrophic factor (GDNF) and neurturin (NTN) belong to a structurally related family of neurotrophic factors. NTN exerts its effect through a multi-component receptor system consisting of the GDNF family receptor alpha 2 (GFRα2), proto-oncogene RET and/or NCAM. GFRα2 is spliced into at least three isoforms, GFRα2a, GFRα2b and GFRα2c. The present study investigated the expression and functional differences of GFRα2 isoforms. These receptor isoforms are differentially expressed in specific human brain regions. Using Neuro2A model, GDNF and NTN promote neurite outgrowth via GFRα2a and GFRα2c, but not GFRα2b. These GFRα2 isoforms regulate different early response genes when stimulated with GDNF and NTN. Interestingly, using co-expression models, GFRα2b inhibits ligand induced neurites outgrowth of GFRα2a and GFRα2c, and also the related receptor, GFRα1a. More intriguingly, ligands activated GFRα2b was also able to attenuate neurite extension induced by an unrelated stimulation using retinoic acid. MAPK activation induced by GDNF was not attenuated by GFRα2b in a co-expression model, while the early response genes expression profile (up-regulation of FosB) was similar to that induced by GFRα2b alone. This study suggest that GFRα2b is not merely a dominant negative isoform, but signals through a yet to be determined mechanism to antagonize and inhibit neuritogenesis. Together, these data suggest a new paradigm for the regulation of growth factor signaling and neurite outgrowth via an inhibitory splice variant of the receptor. / Singapore-MIT Alliance (SMA)

Made available in DSpace on 2010-04-20T21:00:17Z (GMT). No. of bitstreams: 3 danielcosta.pdf.jpg: 11957 bytes, checksum: 9c70f79e4dfbefba6856c68044c195fb (MD5) danielcosta.pdf: 519458 bytes, checksum: d52d6447c9acaaf0d6e32ca4b33c975c (MD5) danielcosta.pdf.txt: 92216 bytes, checksum: 8a01949dc19662a5e29a2dd27de6a755 (MD5) Previous issue date: 2008-01-17T00:00:00Z / Since September 2005 Brazil government sells fixed reais debt on offshore market. Those bonds trade at a price significantly above similar onshore debt. This disparities remains if we consider the differences of costs and tax between onshore and offshore markets. In February 2006 Brazil government exempted foreign investor to pay income tax in local fixed income sovereign debt. This paper quantifies the difference between onshore and offshore brazilian local currency debt yield curve. The analysis is done assuming the point of view of the foreign investor after costs and taxes. We show that a large fraction of the variability of this difference is explained by demand for local currency (measured by exchange rate) and interest rate exposure (local market curve). With this model, we quantified the impact in onshore curve of the foreign investor income tax exemption to be 0.15%. Applying Granger’s causality test (GRANGER, 1969) it was not possible to refute that offshore fixed reais curve cause onshore one. / O governo brasileiro desde setembro de 2005 emite dívida prefixada em reais no mercado externo (offshore). Desde então, este títulos são negociados em taxas significativamente abaixo das taxas dos títulos semelhantes no mercado interno. Estas diferenças permanecem grandes depois de levarmos em consideração as diferenças de custos de impostos entre os dois mercados. Em fevereiro de 2006 o governo brasileiro isentou o investidor estrangeiro do pagamento de imposto de renda no lucro obtido na compra de títulos públicos no mercado interno. Neste trabalho quantificamos, na visão de um investidor estrangeiro, a diferença líquida (descontados custos e impostos) entre as curvas de títulos públicos brasileiros prefixados em reais do mercado interno e externo. Mostramos que esta diferença pode ser largamente explicada por fatores como demanda pela moeda local (representada pela taxa de câmbio reais contra dólar) e nível de taxa de juros (representada pela curva interna). Utilizando o modelo proposto quantificamos em 0.15% o impacto na curva interna da medida que liberou o investidor estrangeiro do pagamento de imposto de renda. Aplicamos teste de causalidade de GRANGER (1969) e não conseguimos rejeitar a hipótese de que a curva prefixada externa em reais causa a curva interna.

Submitted by Renan Brito (renanbrito@hotmail.com) on 2011-08-02T01:26:30Z No. of bitstreams: 1 Tese - Mestrado FGV.pdf: 873176 bytes, checksum: 2dd9a6c54d3362dca3aa5c18f4d394b2 (MD5) / Approved for entry into archive by Vitor Souza (vitor.souza@fgv.br) on 2011-08-02T12:54:06Z (GMT) No. of bitstreams: 1 Tese - Mestrado FGV.pdf: 873176 bytes, checksum: 2dd9a6c54d3362dca3aa5c18f4d394b2 (MD5) / Made available in DSpace on 2011-09-20T20:40:47Z (GMT). No. of bitstreams: 1 Tese - Mestrado FGV.pdf: 873176 bytes, checksum: 2dd9a6c54d3362dca3aa5c18f4d394b2 (MD5) Previous issue date: 2011-05-30 / Um dos grandes desafios na gestão de uma carteira de renda fixa passa pela estimação da curva de juros dos títulos que a compõe. Sua correta estimação e a identificação dos fatores de risco associados a estes títulos são imprescindíveis para uma boa gestão de uma carteira de renda fixa, assim como para o correto apreçamento dos ativos. O presente trabalho tem por objetivo estimar a curva de juros real da economia brasileira a partir de um conjunto de títulos negociados no mercado. Os títulos em questão são as notas do tesouro nacional série B (NTN-B), que tem sua rentabilidade vinculada à variação da inflação (IPCA), acrescida de juros definidos no momento da compra. Por se tratar de títulos que pagam cupom não se pode observar num primeiro momento sua estrutura a termo, nesse sentido, serão apresentados modelos capazes de extrair a curva 'zero cupom' a partir destes títulos e estimar a estrutura a termo da taxa de juros real. Através da análise de componentes principais será possível identificar os principais fatores responsáveis por movimentos na curva estimada e consequentemente no preço do título. Alguns cenários macroeconômicos serão elaborados de forma a estudar o comportamento dos títulos frente a choques nesses fatores (análise de sensibilidade). A elaboração de cenários e a análise das prováveis trajetórias para o preço deste título auxiliarão na gestão de carteiras de títulos de renda fixa.

Integrating Terrestrial and Non-Terrestrial Networks (NTNs) within Beyond-5G (B5G) and future 6G ecosystems represents a transformative advancement in achieving ubiquitous, resilient, and scalable communication services. NTNs, including Low Earth Orbit (LEO) satellites, Unmanned Aerial Vehicles (UAVs), and High Altitude Platform Systems (HAPS), extend traditional terrestrial networks by providing continuous connectivity in remote, underserved, and connection-critical scenarios such as disaster-hit regions and rural areas. This thesis deals with an end-to-end cloud-native framework that leverages cutting-edge technologies, including Multi-Access Edge Computing (MEC), Software Defined Networking (SDN), Network Function Virtualization (NFV), blockchain, and advanced AI/ML models, to enhance service availability, security, and Quality of Service (QoS) in 3D NTN environments. The research first explores the deployment of disaggregated Next-Generation Radio Access Networks (NGRANs) across terrestrial and non-terrestrial domains using a Kubernetes-based architecture. A Graph Neural Network (GNN) model is developed to monitor and manage these networks, detecting link failures and optimizing traffic routing paths between terrestrial and satellite components. The GNN model achieves an 85% accuracy in link failure detection and significantly reduces end-to-end delays in NTN deployments, highlighting the potential of AI-driven network management in enhancing overall network resilience. To address the challenge of dynamic resource management in NTNs, this thesis investigates the implementation of functional splits, such as F1 and E1 interfaces, between terrestrial control units (gNB-CU) and satellite-based distributed units (gNB-DU). The study employs Long Short-Term Memory (LSTM) neural networks to predict resource utilization, specifically CPU, memory, and bandwidth of satellite payloads. These predictive models enable proactive monitoring and resource allocation decisions, ensuring efficient use of limited computational resources and maintaining high levels of network performance. Security remains a critical concern in NTNs due to decentralized and open 5G satellite communications. A blockchain-based authentication framework is proposed to mitigate these risks, enhancing the security of data exchanges and remote firmware updates in LEO satellite constellations. Blockchain technology provides a decentralized, transparent, and immutable security framework, improving authentication efficiency and protecting against unauthorized access, though with trade-offs in network performance, such as increased latency and reduced throughput. This approach makes the hybrid B5G NTN network secure, reinforcing the integrity and confidentiality of communication channels, which is essential for emerging services and applications. Furthermore, this thesis comprehensively evaluates MEC-based experimental testbeds that demonstrate service resiliency in NTNs during terrestrial network outages. The MEC deployments allow seamless transitions to satellite access networks, ensuring service continuity and improving QoS. These testbeds showcase the capability of cloud native technologies in maintaining service availability, highlighting their critical role in resilient NTN networks. The findings of this thesis demonstrate that integrating cloud-native architectures, blockchain-based security mechanisms, and advanced AI/ML models significantly enhances the resilience, security, and resource efficiency of NTNs. These innovations pave the way for robust, adaptive, and secure communication systems, supporting the seamless deployment of critical B5G and 6G applications across diverse and challenging environments. This research provides valuable insights into designing and implementing resilient NTNs, setting the foundation for future advancements in global connectivity and intelligent network management.

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