Investigating the CD4+ T cell response to infection with Trypanosoma brucei

African trypanosomes are a protozoan parasite with the ability to cause disease states in both humans and animals; rendering them an important and relevant subject of study. These diseases have a vast socioeconomic impact upon the African continent and are perpetuated in part by the parasite's ability to evade the adaptive immune response. This thesis describes CD4+ T cell response to trypanosome infection, through the use of murine infection models and in vitro assays.

Adaptive Mechanisms of an Estuarine Synechococcus based on Genomics, Transcriptomics, and Proteomics

Picocyanobacteria are important phytoplankton and primary producers in the ocean. Although extensive work has been conducted for picocyanobacteria (i.e. Synechococcus and Prochlorococcus) in coastal and oceanic waters, little is known about those found in estuaries like the Chesapeake Bay. Synechococcus CB0101, an estuarine isolate, is more tolerant to shifts in temperature, salinity, and metal toxicity than coastal and oceanic Synechococcus strains, WH7803 and WH7805. Further, CB0101 has a greater sensitivity to high light intensity, likely due to its adaptation to low light environments. A complete and annotated genome sequence of CB0101 was completed to explore its genetic capacity and to serve as a basis for further molecular analysis. Comparative genomics between CB0101, WH7803, and WH7805 show that CB0101 contains more genes involved in regulation, sensing, and stress response. At the transcript and protein level, CB0101 regulates its metabolic pathways, transport systems, and sensing mechanisms when nitrate and phosphate are limited. Zinc toxicity led to oxidative stress and a global down regulation of photosystems and the translation machinery. From the stress response studies seven chromosomal toxin-antitoxin (TA) genes, were identified in CB0101, which led to the discovery of TA genes in several marine Synechococcus strains. The activation of the relB2/relE1 TA system allows CB0101 to arrest its growth under stressful conditions, but the growth arrest is reversible, once the stressful environment dissipates. The genome of CB0101 contains a relatively large number of genomic island (GI) genes compared to known marine Synechococcus genomes. Interestingly, a massive shutdown (255 out of 343) of GI genes occurred after CB0101 was infected by a lytic phage. On the other hand, phage-encoded host-like proteins (hli, psbA, ThyX) were highly expressed upon phage infection. This research provides new evidence that estuarine Synechococcus like CB0101 have inherited unique genetic machinery, which allows them to be versatile in the estuarine environment.

Adaptive lighting design as a holistic approach to public lighting

Dissertação para obtenção do grau de Doutor em Design, apresentada na Universidade de Lisboa - Faculdade de Arquitetura.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Prevalence of SOS-mediated control of integron integrase expression as an adaptive trait of chromosomal and mobile integrons

BACKGROUND Integrons are found in hundreds of environmental bacterial species, but are mainly known as the agents responsible for the capture and spread of antibiotic-resistance determinants between Gram-negative pathogens. The SOS response is a regulatory network under control of the repressor protein LexA targeted at addressing DNA damage, thus promoting genetic variation in times of stress. We recently reported a direct link between the SOS response and the expression of integron integrases in Vibrio cholerae and a plasmid-borne class 1 mobile integron. SOS regulation enhances cassette swapping and capture in stressful conditions, while freezing the integron in steady environments. We conducted a systematic study of available integron integrase promoter sequences to analyze the extent of this relationship across the Bacteria domain. RESULTS Our results showed that LexA controls the expression of a large fraction of integron integrases by binding to Escherichia coli-like LexA binding sites. In addition, the results provide experimental validation of LexA control of the integrase gene for another Vibrio chromosomal integron and for a multiresistance plasmid harboring two integrons. There was a significant correlation between lack of LexA control and predicted inactivation of integrase genes, even though experimental evidence also indicates that LexA regulation may be lost to enhance expression of integron cassettes. CONCLUSIONS Ancestral-state reconstruction on an integron integrase phylogeny led us to conclude that the ancestral integron was already regulated by LexA. The data also indicated that SOS regulation has been actively preserved in mobile integrons and large chromosomal integrons, suggesting that unregulated integrase activity is selected against. Nonetheless, additional adaptations have probably arisen to cope with unregulated integrase activity. Identifying them may be fundamental in deciphering the uneven distribution of integrons in the Bacteria domain.

The conjugate gradient partitioned block frequency-domain for multichannel adaptive filtering

The conjugate gradient is the most popular optimization method for solving large systems of linear equations. In a system identification problem, for example, where very large impulse response is involved, it is necessary to apply a particular strategy which diminishes the delay, while improving the convergence time. In this paper we propose a new scheme which combines frequency-domain adaptive filtering with a conjugate gradient technique in order to solve a high order multichannel adaptive filter, while being delayless and guaranteeing a very short convergence time.