Mecanismos de inflamação brônquica resultantes da exposição a factores ambientais

RESUMO Tratando-se a asma de uma doença respiratória, desde há várias décadas que tem sido abordada a hipótese de que factores ambientais, nomeadamente os relacionados com a qualidade do ar inalado, possam contribuir para o seu agravamento. Para além dos aeroalergenos, outros factores ambientais como a poluição atmosférica estarão associados às doenças respiratórias. O ar respirado contém uma variedade de poluentes atmosféricos, provenientes quer de fontes naturais quer de origem antropogénica, nomeadamente de actividades industriais, domésticas ou das emissões de veículos. Estes poluentes, tradicionalmente considerados como um problema de foro ambiental, têm sido cada vez mais encarados como um problema de saúde pública. Também a qualidade do ar interior, tem sido associada a queixas respiratórias, não só em termos ocupacionais mas também em exposições domésticas. Dentro dos principais poluentes, encontramos a matéria particulada (como as PM10), o O3, NO2, e os compostos orgânicos voláteis (COVs). Se é verdade que os três primeiros têm como principais fontes de exposição a combustão fóssil associada aos veículos automóveis, já os COVs (como o benzeno, tolueno, xileno, etilbenzeno e formaldeído) são poluentes mais característicos do ar interior. Os mecanismos fisiopatológicos subjacentes à agressão dos poluentes do ar não se encontram convenientemente esclarecidos. Pensa-se que após a sua inalação, induzam um grau crescente de stress oxidativo que será responsável pelo desenvolvimento da inflamação das vias aéreas. A progressão do stress oxidativo e da inflamação, associarse- ão posteriormente a lesão local (pulmonar) e sistémica. Neste trabalho pretendeu-se avaliar os efeitos da exposição individual a diversos poluentes, do ar exterior e interior, sobre as vias aéreas, recorrendo a parâmetros funcionais, inflamatórios e do estudo do stress oxidativo. Neste sentido, desenvolveu-se um estudo de painel na cidade de Viseu, em que foram acompanhadas durante 18 meses, 51 crianças com história de sibilância, identificadas pelo questionário do estudo ISAAC. As crianças foram avaliadas em quatro Visitas (quatro medidas repetidas), através de diversos exames, que incluíram execução de espirometria com broncodilatação, medição ambulatória do PEF, medição de FENO e estudo do pH no condensado brônquico do ar exalado. O estudo dos 8-isoprostanos no condensado brônquico foi efectuado somente em duas Visitas, e o do doseamento de malonaldeído urinário somente na última Visita. Para além da avaliação do grau de infestação de ácaros do pó do colchão, para cada criança foi calculado o valor de exposição individual a PM10, O3, NO2, benzeno, tolueno, xileno, etilbenzeno e formaldeído, através de uma complexa metodologia que envolveu técnicas de modelação associadas a medições directas do ar interior (na casa e escola da criança) e do ar exterior. Para a análise de dados foram utilizadas equações de estimação generalizadas com uma matriz de correlação de trabalho uniforme, com excepção do estudo das associações entre poluentes, 8-isoprostanos e malonaldeído. Verificou-se na análise multivariável a existência de uma associação entre o agravamento dos parâmetros espirométricos e a exposição aumentada a PM10, NO2, benzeno, tolueno e etilbenzeno. Foram também encontradas associações entre diminuição do pH do EBC e exposição crescente a PM10, NO2, benzeno e etilbenzeno e associações entre valores aumentados de FENO e exposição a etilbenzeno e tolueno. O benzeno, o tolueno e o etilbenzeno foram associados com maior recurso a broncodilatador nos 6 meses anteriores à Visita e o tolueno com deslocações ao serviço de urgência. Os resultados dos modelos de regressão que incluíram o efeito do poluente ajustado para o grau de infestação de ácaros do pó foram, de uma forma geral, idênticos ao da análise multivariável anterior, com excepção das associações para com o FENO. Nos modelos de exposição com dois poluentes, com o FEV1 como variável resposta, somente o benzeno persistiu com significado estatístico. No modelo com dois poluentes tendo o pH do EBC como variável resposta, somente persistiram as PM10. Os 8-isoprostanos correlacionaram-se com alguns COVs, designadamente etilbenzeno, xileno, tolueno e benzeno. Os valores de malonaldeído urinário não se correlacionaram com os valores de poluentes. Verificou-se no entanto que de uma forma geral, e em particular mais uma vez para os COVs, as crianças mais expostas a poluentes, apresentaram valores superiores de malonaldeído na urina. Verificou-se que os poluentes do ar em geral, e os COVs em particular, se associaram com uma deterioração das vias aéreas. A exposição crescente a poluentes associou-se não só com obstrução brônquica, mas também com FENO aumentado e maior acidez das vias aéreas. A exposição crescente a COVs correlacionou-se com um maior stress oxidativo das vias aéreas (medido pelos 8-isoprostanos). As crianças com exposição superior a COVs apresentaram maiores valores de malonaldeído urinário. Este trabalho sugere uma associação entre exposição a poluentes, inflamação das vias aéreas e stress oxidativo. Vem reforçar o interesse dos poluentes do ar, nomeadamente os associados a ambientes interiores, frequentemente esquecidos e que poderão ser explicativos do agravamento duma criança com sibilância.-----------ABSTRACT: Asthma is a chronic respiratory disease that could be influenced by environmental factors, as allergens and air pollutants. The air breathed contains a diversity of air pollutants, both from natural or anthropogenic sources. Atmospheric pollution, traditionally considered an environmental problem, is nowadays looked as an important public health problem. Indoor air pollutants are also related with respiratory diseases, not only in terms of occupational exposures but also in domestic activities. Particulate matter (such as PM10), O3, NO2 and volatile organic compounds (VOCs) are the main air pollutants. The main source for PM10, O3, NO2 exposure is traffic exhaust while for VOCs (such as benzene, toluene, xylene, ethylbenzene and phormaldehyde) the main sources for exposure are located in indoor environments. The pathophysiologic mechanisms underlying the aggression of air pollutants are not properly understood. It is thought that after inhalation, air pollutants could induce oxidative stress, which would be responsible for airways inflammation. The progression of oxidative stress and airways inflammation, would contribute for the local and systemic effects of the air pollutants. The present study aimed to evaluate the effects of individual exposure to various pollutants over the airways, through lung function tests, inflammatory and oxidative stress biomarkers. In this sense, we developed a panel study in the city of Viseu, that included 51 children with a history of wheezing. Those children that were identified by the ISAAC questionnaire, were followed for 18 months. Children were assessed four times (four repeated measures) through the following tests: spirometry with bronchodilation test, PEF study, FENO evaluation and exhaled breath condensate pH measurement. 8-isoprostane in the exhaled breath condensate were also measured but only in two visits. Urinary malonaldehyde measurement was performed only in the last visit. Besides the assessment of the house dust mite infestation, we calculated for each child the value of individual exposure to a wide range of pollutants: PM10, O3, NO2, benzene, toluene, xylene, ethyl benzene and formaldehyde. This strategy used a complex methodology that included air pollution modelling techniques and direct measurements indoors (homes and schools) and outdoors. Generalized estimating equations with an exchangeable working correlation matrix were used for the analysis of the data. Exceptions were for the study of associations between air pollutants, malonaldehyde and 8-isoprostanes. In the multivariate analysis we found an association between worsening of spirometric outcomes and increased exposure to PM10, NO2, benzene, toluene and ethylbenzene. In the multivariate analysis we found also negative associations between EBC pH and exposure to PM10, NO2, benzene, ethylbenzene and positive associations between FENO and exposure to ethylbenzene and toluene. Benzene, toluene and ethylbenzene were associated with increased use of bronchodilator in the 6 months prior to the visit and toluene with emergency department visits. Results of the regression models that included also the effect of the pollutant adjusted for the degree of infestation to house dust mites, were identical to the previous models. Exceptions were for FENO associations. In the two-pollutant models, with the FEV1 as dependent variable, only benzene persisted with statistical significance. In the two pollutant model with pH of EBC as dependent variable, only PM10 persisted. 8-isoprostanes were well correlated with some VOCs, namely with ethylbenzene, xylene, toluene and benzene. Urinary malonaldehyde did not present any correlation with air pollutants exposure. However, those children more exposed to air pollutants (namely to VOCs), presented higher values of malonaldehyde. It was found that air pollutants in general, and namely VOCs, were associated with deterioration of the airways. The increased exposure to air pollutants was associated not only with airways obstruction, but also with increased FENO and higher acidity of the airways. The increased exposure to VOCs was correlated with increased airways oxidative stress (measured by 8-isoprostane). Children with higher levels of exposure to VOCs had higher values of urinary malonaldehyde. This study suggests a relation between air pollution, airways inflammation and oxidative stress. It suggests also that attention should be dedicated to air quality as air pollutants could cause airways deterioration.

The impact of sizeof the firm and exchange rate in the export propensity of domestic and foreign owned firms in a developing country: A study of the Brazilian exporters

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.