Desenvolvimento de um biossensor de ADN integrado num chip de microfluídica

Dissertação para obtenção do Grau de Mestre em Engenharia BiomédicaOs biossensores têm vindo a captar elevado interesse devido à necessidade dos laboratórios de diagnóstico em disporem de métodos de análise rápidos, precisos e pouco dispendiosos. Nesse contexto, esta dissertação aborda o desenvolvimento de um biossensor de microfluídica para detecção colorimétrica de ADN, constituído por um chip de microfluídica inserido numa plataforma optoelectrónica. O método de detecção é baseado no comportamento colorimétrico de uma solução de nanopartículas de ouro funcionalizadas com sequências simples de ADN, com a adição de sal. Quando há complementaridade, as nanopartículas não agregam, mantendo-se a solução com a mesma coloração vermelha (teste positivo), caso contrário, há agregação e a solução torna-se azul (teste negativo). O dispositivo de microfluídica foi fabricado em PDMS por replica molding, recorrendo a moldes de SU-8 produzidos por fotolitografia. O processo de microfabricação foi optimizado de forma a obter moldes com elevado rácio entre área e espessura das estruturas e a manter a perfeita reprodutibilidade das réplicas (introdução de um molde intermédio de epóxi). Este dispositivo foi inserido numa plataforma optoelectrónica constituída por uma fonte de luz (LED) e um fotodetector (fotodíodo), integrados através de fibras ópticas, onde foram testadas várias geometrias e configurações de chips. Os resultados mostram que este biossensor detecta mudanças colorimétricas para caminhos ópticos de 10 mm (451 nL) até 0,5 mm (315 nL), sendo que a discriminação das duas soluções aumenta com o percurso óptico. Os melhores resultados foram obtidos para um percurso óptico de 4 mm, para o qual se obtém uma clara distinção de soluções com necessidade de apenas 365 nL para encher o microcanal. A simplicidade dos métodos e materiais utilizados, incluindo a possibilidade de reduzir bastante o volume de reagentes, traduzem-se numa contribuição relevante deste dispositivo no âmbito dos métodos de detecção de ADN

Sistemas de veiculação de fármacos antimicrobianos para tratamento da osteomielite: uma revisão sistemática

Mestrado em Farmácia - Área de especialização: Farmacologia e Farmacoterapia AvançadaA osteomielite é uma infeção, geralmente bacteriana, do osso com uma inflamação simultânea dos tecidos adjacentes, conduzindo à destruição óssea. Muitos antibióticos são limitados por índices terapêuticos estreitos e toxicidade. Estas limitações podem ser ultrapassadas através da utilização de um sistema de administração, que modifica a distribuição do medicamento no organismo, direcionando-o para o local desejado e controlando a sua libertação. O objetivo geral desta dissertação é caracterizar os sistemas de veiculação de fármacos antimicrobianos para o osso e potencial aplicação no tratamento da osteomielite. A pergunta de investigação definida foi “os sistemas de veiculação local de fármacos melhoram os resultados do tratamento em doentes com osteomielite, em comparação com os tratamentos sem recurso a sistemas de libertação controlada?”. A metodologia escolhida foi a PRISMA. As fontes de informação selecionadas foram a Pubmed, Cochrane e Web of Science. As referências das bases de dados foram combinadas e processadas de acordo com os critérios de elegibilidade. Dos 78 estudos encontrados, 22 foram incluídos nesta revisão sistemática. Após a revisão dos estudos, parece que o Polimetilmetacrilato (PMMA) é uma boa escolha quanto à estabilidade mecânica e segurança. A escolha do sulfato de cálcio (SC) deve-se aparentemente às desvantagens do PMMA, e a adição de hidroxiapatite é aparentemente uma tentativa bem-sucedida de otimização do SC e colmatar as suas limitações. O principal objetivo da aplicação de um sistema de veiculação de fármacos parece ser minimizar a abordagem cirúrgica no controlo da doença, com um interesse crescente em desenvolver uma metodologia de um só ato cirúrgico. Apesar de muitas abordagens cirúrgicas estarem disponíveis, ainda não há consenso estabelecido sobre o tratamento ideal. As perspetivas futuras incluem sistemas locais de administração que satisfaçam as necessidades de diferentes doentes.ABSTRACT - Osteomyelitis is an infection, usually bacteria, of bone a simultaneous inflammation involving the surrounding tissues which lead to bone destruction. Many antibiotics are limited by narrow therapeutic windows and toxicity. These handicaps can be circumvented through the use of an appropriately designed delivery system, which can modify the distribution of the drug in the body by targeting it to the desired site and by controlling its release. The main purpose of this dissertation is to characterize the different drug delivery systems used to administer antimicrobial drugs to treat osteomyelitis. A search question was conceived in the PICO (Patient/Population, Intervention, Comparison, and Outcomes) strategy, resulting in: Are drug delivery systems an advantageous approach for local treatment in osteomyelitis clinical studies, resulting in patients’ health improvement? The methodology chose the PRISMA statement. The information sources chosen were Pubmed, Cochrane, and Web of Science. References from the databases were combined and processed according to the eligibility criteria. Of the 77 studies screened, 22 were included in this systematic review. After reviewing the studies, it seems that the choice of polymethyl methacrylate (PMMA) is mainly based on it being the best option for mechanical stabilization and safety. The choice of calcium sulfate apparently is due to PMMA disadvantages, and the addition of hydroxyapatite is an attempt, successful in the studies reviewed, to improve the use of calcium sulfate and its limitations when used alone. The main purpose of using a delivery system seems to be to minimize the surgical approach in the management of the disease, with an increasing interest in developing a one-stage procedure. Even though many surgical approaches are available, there is still no established consensus on the ideal treatment. Future perspectives include local delivery systems that meet different patients’ needs.N/

Methods for Detecting and Classifying Weeds, Diseases and Fruits Using AI to Improve the Sustainability of Agricultural Crops: A Review

The rapid growth of the world’s population has put significant pressure on agriculture to meet the increasing demand for food. In this context, agriculture faces multiple challenges, one of which is weed management. While herbicides have traditionally been used to control weed growth, their excessive and random use can lead to environmental pollution and herbicide resistance. To address these challenges, in the agricultural industry, deep learning models have become a possible tool for decision-making by using massive amounts of information collected from smart farm sensors. However, agriculture’s varied environments pose a challenge to testing and adopting new technology effectively. This study reviews recent advances in deep learning models and methods for detecting and classifying weeds to improve the sustainability of agricultural crops. The study compares performance metrics such as recall, accuracy, F1-Score, and precision, and highlights the adoption of novel techniques, such as attention mechanisms, single-stage detection models, and new lightweight models, which can enhance the model’s performance. The use of deep learning methods in weed detection and classification has shown great potential in improving crop yields and reducing adverse environmental impacts of agriculture. The reduction in herbicide use can prevent pollution of water, food, land, and the ecosystem and avoid the resistance of weeds to chemicals. This can help mitigate and adapt to climate change by minimizing agriculture’s environmental impact and improving the sustainability of the agricultural sector. In addition to discussing recent advances, this study also highlights the challenges faced in adopting new technology in agriculture and proposes novel techniques to enhance the performance of deep learning models. The study provides valuable insights into the latest advances and challenges in process systems engineering and technology for agricultural activities

Fuzzy Logic Decision Support System to Predict Peaches Marketable Period at Highest Quality

Food waste occurs from harvesting to consumption. Applying procedures and technologies, changing attitudes, and promoting awareness have positive social, economic, and environmental impacts that can contribute to reducing food waste. The paper presents a decision support system (DSS) to predict the quality evolution of fruits and vegetables, particularly of peaches, and estimate its commercialization period at the highest overall perceived quality by consumers, thus contributing to reducing food waste. The Fuzzy Logic DSS predicts the evolution of the physical-chemical parameters of peaches (hardness, soluble solids content, and acidity) depending on the cultivar (Royal Summer and Royal Time), storage time, and temperature. As the range of the values of these physical-chemical parameters of peaches that consumers perceive to be at their highest quality are known, the DSS predicts the marketable period in days. Case studies were developed to analyze the influence of each physical-chemical parameter on the commercialization days (number and time to start). It is concluded that temperature is the most important parameter for fruit conservation. A low value of conservation temperature allows for the significant extension of the time that peaches can be sold at the highest quality. Hardness is used to determine the harvest date since it is an index of fruit ripeness. The same conclusion is obtained for the influence of the soluble solids content. The influence of acidity on marketable days is less than the other physical-chemical parameters. This DSS helps retailers to sell their peaches at the highest quality with benefits for all parties. It also helps in the decision-making concerning the actions to take when fruits are reaching the end of their highest quality by predicting the range of the commercialization days. This formulation can be extended to other fruits and vegetables and in the last instance contribute to the reduction of food loss and waste, consequently promoting social, economic, and environmental aspects of our daily life

Fuzzy Logic Decision Support System to Predict Peaches Marketable Period at Highest Quality

Food waste occurs from harvesting to consumption. Applying procedures and technologies, changing attitudes, and promoting awareness have positive social, economic, and environmental impacts that can contribute to reducing food waste. The paper presents a decision support system (DSS) to predict the quality evolution of fruits and vegetables, particularly of peaches, and estimate its commercialization period at the highest overall perceived quality by consumers, thus contributing to reducing food waste. The Fuzzy Logic DSS predicts the evolution of the physical-chemical parameters of peaches (hardness, soluble solids content, and acidity) depending on the cultivar (Royal Summer and Royal Time), storage time, and temperature. As the range of the values of these physical-chemical parameters of peaches that consumers perceive to be at their highest quality are known, the DSS predicts the marketable period in days. Case studies were developed to analyze the influence of each physical-chemical parameter on the commercialization days (number and time to start). It is concluded that temperature is the most important parameter for fruit conservation. A low value of conservation temperature allows for the significant extension of the time that peaches can be sold at the highest quality. Hardness is used to determine the harvest date since it is an index of fruit ripeness. The same conclusion is obtained for the influence of the soluble solids content. The influence of acidity on marketable days is less than the other physical-chemical parameters. This DSS helps retailers to sell their peaches at the highest quality with benefits for all parties. It also helps in the decision-making concerning the actions to take when fruits are reaching the end of their highest quality by predicting the range of the commercialization days. This formulation can be extended to other fruits and vegetables and in the last instance contribute to the reduction of food loss and waste, consequently promoting social, economic, and environmental aspects of our daily life