Estudo numérico do escoamento em descarregadores por orifício

Atualmente, no estudo do comportamento de descarregadores de cheias por orifício, é necessário conhecer as pressões ao longo do descarregador, para várias alturas de água na albufeira. Este tipo de estudos tem sido usualmente realizado recorrendo a ensaios experimentais. No entanto, a utilização de modelos numéricos para a simulação do escoamento em estruturas hidráulicas encontra-se numa fase emergente. Neste sentido, a presente dissertação pretende apresentar um estudo numérico relativo ao escoamento em descarregadores de cheias por orifício. Por forma a efetuar o estudo numérico, foi utlizado o programa comercial de CFD FLOW-3D®, reproduzindo um modelo reduzido construído no Laboratório Nacional de Engenharia Civil (LNEC) correspondente a um descarregador por orifício. Para a realização das simulações numéricas foi necessário definir o objeto de estudo, a malha de cálculo, as condições de fronteira e as propriedades do fluido e objeto de modo a reproduzir as situações ensaiadas experimentalmente no LNEC. A proximidade dos resultados experimentais e numéricos para vários níveis de água na albufeira permitiu validar o modelo numérico para este tipo de escoamentos no interior do orifício.

Optimization of a multielectrode array (MEA)-based approach to study the impact of Aβ on the SH-SY5Y cell line

The human brain stores, integrates, and transmits information recurring to millions of neurons, interconnected by countless synapses. Though neurons communicate through chemical signaling, information is coded and conducted in the form of electrical signals. Neuroelectrophysiology focus on the study of this type of signaling. Both intra and extracellular approaches are used in research, but none holds as much potential in high-throughput screening and drug discovery, as extracellular recordings using multielectrode arrays (MEAs). MEAs measure neuronal activity, both in vitro and in vivo. Their key advantage is the capability to record electrical activity at multiple sites simultaneously. Alzheimer’s disease (AD) is the most common neurodegenerative disease and one of the leading causes of death worldwide. It is characterized by neurofibrillar tangles and aggregates of amyloid-β (Aβ) peptides, which lead to the loss of synapses and ultimately neuronal death. Currently, there is no cure and the drugs available can only delay its progression. In vitro MEA assays enable rapid screening of neuroprotective and neuroharming compounds. Therefore, MEA recordings are of great use in both AD basic and clinical research. The main aim of this thesis was to optimize the formation of SH-SY5Y neuronal networks on MEAs. These can be extremely useful for facilities that do not have access to primary neuronal cultures, but can also save resources and facilitate obtaining faster high-throughput results to those that do. Adhesion-mediating compounds proved to impact cell morphology, viability and exhibition of spontaneous electrical activity. Moreover, SH-SY5Y cells were successfully differentiated and demonstrated acute effects on neuronal function after Aβ addition. This effect on electrical signaling was dependent on Aβ oligomers concentration. The results here presented allow us to conclude that the SH-SY5Y cell line can be successfully differentiated in properly coated MEAs and be used for assessing acute Aβ effects on neuronal signaling.