Finding Aedes aegypti in a natural breeding site in an urban zone, Sao Paulo, Southeastern Brazil

ABSTRACT This is the description of how nine Aedes aegypti larvae were found in a natural breeding site in the Pinheiros neighborhood, city of Sao Paulo, SP, Southeastern Brazil. The record was conducted in December 2014, during an entomological surveillance program of dengue virus vectors, with an active search of potential breeding sites, either artificial or natural. Finding Ae. aegypti larvae in a tree hole shows this species’ ability to use both artificial and natural environments as breeding sites and habitats, which points towards the importance of maintaining continuous surveillance on this mosquito in all kinds of water-holding containers.

Antigen characterization of vector-borne and cultured metacyclic trypomastigotes of Trypanosoma cruzi

Metacyclic trypomastigotes ol the CL strain of Trypanosoma cruzi obtained from triatomid vectors and from axenic cultures were comparatively analysed as to their antigen make-up and immunogenic characteristics. They were found to be similar by the various parameters examined. Thus, sera of mice immunized with either one of the two metacyclic types precipitated a 82Kd surface protein from 131I-labeled culture metacyclics. Sera of mice protected against acute T. cruzi infection by immunization with killed culture metacyclics of a different strain (G) recognized, by immunoblotting, a 77Kd protein in both types of CL strain metacyclics. A monoclonal antibody raised against G strain metacyclics, and specific for metacyclic stages of this strain, reacted with both CL strain metacyclic types. Both metacyclic forms were similarly Iysed by various anti-T. cruzi sera, in a complement-mediated reaction.

Dynamics of transmission of Trypanosoma cruzi in a rural area of Argentina: III. Persistence of T. cruzi parasitemia among canine reservoirs in a two-year follow-up

A new cross-sectional survey of household- associated mongrel dogs as well as follow-up of previously parasitemic individuals was carried out in 1984 toy means of xenodiagnosis and serologic techniques to get a deeper insight into the relationship of T. cruzi parasitemia and age among canine hosts in a rural area of Argentina. Persistence of detectable parasitemia was age-independent, or at most, loosely related to age, confirming the pattern observed in 1982. Similarly no significant age-decreasing effect was recorded among seropositive dogs in: a) the probability of detecting parasites in a 2-year follow-up; b) their intensity of infectiousness (=infective force) for T. infestans 3rd-4th instar nymphs, as measured by the percentage of infected bugs observed in each dog xenodiagnosis. Moreover, not only was the infective force of seropositive dogs for bugs approximately constant through lifetime, but it was significantly higher than the one recorded for children in the present survey, and for human people by other researchers. Therefore, and since T. infestans field populations show high feeding frequencies on dogs, the latter are expected to make the greatest contribution to the pool of infected vectors in the rural household of Argentina. This characteristic should be sufficient to involve canine reservoirs definitely as a risk factor for human people residing in the same house. The increased severity of parasitemia observed among dogs in this survey may be related to the acute undernutrition characteristic of canine populations of poor rural areas in our country, which is expected to affect the ability of the host to manage the infection.

Gestão integrada de ativos num contexto real

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Manutenção

Recent occurence of human infection by Rocio arbovirus in Ribeira Valley, Brazil

The presence of IgM antibodies to Rocio in sera of two children from rural area of Ribeira Valley, Brazil, was detected by MAC-ELISA. This new arbovirus of the Flaviviridae family was responsible for an extensive encephalitis epidemic that occurred in the region in 1975-1977. Since 1980 no human disease caused by this virus has been diagnosed. An improvement on surveillance of Rocio infections and on the researches for virus identification in suspected vectors and reservoirs is necessary.

The ecology of Triatoma sordida in natural environments in two different regions of the state of Minas Gerais, Brazil

A study was undertaken about T. sordida in the natural environment in two different regions of the state of Minas Gerais: Itapagipe (Triângulo), an area of cerrado modified by the formation of fields of pasture and agriculture, and Mato Verde (north) an area of transition between caatinga and cerrado with profound deforestation in the last years due to the expansion of cotton cultivation. In both regions the principal ecotopes identified were hollow trees and the bark of live or dead trees, where the occurrence of a food source is not frequent. In this environment, the triatomines utilize various food sources; opposums appear to represent an important source of infection. In the north of Minas, a greater concentration of reservoirs and vectors was observed than in the Triángulo which could explain the higher level of infection of the triatomines in the north. Close attention to the process of domiciliation of T. sordida in the north of Minas is recommended where an extensive intervention by man in the natural environment has occurred and where a rise in the population of triatomines in the peridomestic environment has been observed in recent years.

Proposal for shared services performance management model applied to portugueses public administration

Comunicação apresentada no 8º Congresso Nacional de Administração Pública - Desafios e Soluções, em Carcavelos de 21 a 22 de Novembro de 2011.

Chagas' disease in the Brazilian Amazon: I - a short review

At least eighteen species of triatominae have been found in the Brazilian Amazon, nine of them naturally infected with Trypanosoma cruzi or "cruzi-like" trypanosomes and associated with numerous wild reservoirs. Despite the small number of human cases of Chagas' disease described to date in the Brazilian Amazon the risk that the disease will become endemic in this area is increasing for the following reasons: a) uncontrolled deforestation and colonization altering the ecological balance between reservoir hosts and wild vectors; b) the adaptation of reservoir hosts of T.cruzi and wild vectors to peripheral and intradomiciliary areas, as the sole feeding alternative; c) migration of infected human population from endemic areas, accompanied by domestic reservoir hosts (dogs and cats) or accidentally carrying in their baggage vectors already adapted to the domestic habitat. In short, risks that Chagas' disease will become endemic to the Amazon appear to be linked to the transposition of the wild cycle to the domestic cycle in that area or to transfer of the domestic cycle from endemic areas to the Amazon.

Magma flow pattern in dykes of the Azores revealed by ansiotropy of magnetic susceptibility

The localization of magma melting areas at the lithosphere bottom in extensional volcanic domains is poorly understood. Large polygenetic volcanoes of long duration and their associated magma chambers suggest that melting at depth may be focused at specific points within the mantle. To validate the hypothesis that the magma feeding a mafic crust, comes from permanent localized crustal reservoirs, it is necessary to map the fossilized magma flow within the crustal planar intrusions. Using the AMS, we obtain magmatic flow vectors from 34 alkaline basaltic dykes from São Jorge, São Miguel and Santa Maria islands in the Azores Archipelago, a hot-spot related triple junction. The dykes contain titanomagnetite showing a wide spectrum of solid solution ranging from Ti-rich to Ti-poor compositions with vestiges of maghemitization. Most of the dykes exhibit a normal magnetic fabric. The orientation of the magnetic lineation k1 axis is more variable than that of the k3 axis, which is generally well grouped. The dykes of São Jorge and São Miguel show a predominance of subhorizontal magmatic flows. In Santa Maria the deduced flow pattern is less systematic changing from subhorizontal in the southern part of the island to oblique in north. These results suggest that the ascent of magma beneath the islands of Azores is predominantly over localized melting sources and then collected within shallow magma chambers. According to this concept, dykes in the upper levels of the crust propagate laterally away from these magma chambers thus feeding the lava flows observed at the surface.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Hyperspectral imagery framework for unmixing and dimensionality estimation

In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Monitorização das concentrações plasmáticas de Efavirenz: critérios de aplicabilidade à prática clínica e efeitos do fármaco a longo termo

Resumo O objectivo geral deste trabalho foi contribuir para optimizar a terapêutica anti-retroviral e o seu impacto na qualidade de vida do indivíduo infectado pelo vírus da imunodeficiência humana. Pretendia-se definir se o análogo não-nucleósido inibidor da transcriptase reversa do vírus da imunodeficiência humana, efavirenz, cumpria os requisitos para ser monitorizado na prática clínica, estabelecer as condições para a sua eventual monitorização e, simultaneamente, investigar outras acções farmacodinâmicas do efavirenz em terapêuticas prolongadas. Os critérios que fundamentam a indicação da monitorização das concentrações plasmáticas de fármacos, em geral, incluem: correlação entre a concentração do fármaco e a eficácia/toxicidade; variabilidade inter-individual elevada; variabilidade intra-individual e janela terapêutica reduzidas e ainda a elevada probabilidade de interacções medicamentosas. A correlação entre concentração plasmática de efavirenz e eficácia/toxicidade era conhecida e o facto de o efavirenz ser substrato, indutor e inibidor do sistema enzimático citocromo P450 e ser utilizado em terapêuticas crónicas e nunca em monoterapia, constituíam fortes argumentos para a aplicação da monitorização terapêutica ao efavirenz. O presente trabalho contribuiu para o conhecimento de outros critérios, nomeadamente, a variabilidade nas concentrações plasmáticas deste fármaco, entre indivíduos e no mesmo indivíduo, e permitiu definir diferentes aspectos para a prática da monitorização terapêutica deste fármaco, entre eles, o volume de plasma necessário, o parâmetro farmacocinético a avaliar e a periodicidade das quantificações. Para se atingirem os objectivos definidos foi necessário, em primeiro lugar, proceder à instalação e validação de um método de quantificação de concentrações de efavirenz, em plasma de indivíduos infectados pelo vírus da imunodeficiência humana: ficou disponível no Laboratório de Farmacologia da Faculdade de Ciências Médicas, um método que permite a monitorização das concentrações plasmáticas de nove fármacos anti-retrovirais (nevirapina, indinavir, amprenavir, atazanavir, ritonavir, efavirenz, lopinavir, saquinavir e nelfinavir). O método desenvolvido está presentemente a ser utilizado na monitorização terapêutica destes fármacos e em estudos Farmacológicos. Esta quantificação é realizada numa única corrida analítica de cromatografia líquida de elevada eficiência, a partir de 0,4 mL de plasma de cada indivíduo e a sua qualidade é avaliada, bianualmente, por uma entidade externa. Posteriormente, com o objectivo de as comparar, procurou-se conhecer a variabilidade entre indivíduos e intra-individual das concentrações lasmáticas do fármaco e concluiu-se que a variabilidade entre indivíduos é superior à intra-individual, o que suporta a monitorização das suas concentrações. Uma vez encontrada uma variabilidade inter-individual elevada, surgiu um outro objectivo específico, que consistiu na identificação de possíveis factores a justificassem. Na presente dissertação foi mostrado que o sexo, idade, peso e etnia não justificam por si só esta variação, não sendo possível o ajuste de dose com base nestas variáveis. Esta conclusão constitui um factor adicional que reforça que a toma da dose recomendada de efavirenz poderá não ser apropriada para todos os indivíduos. A co-infecção pelos vírus da hepatite B e/ou C é comum nesta população e poderia ser um dos factores implicados nesta variabilidade farmacocinética. A realização do presente trabalho permitiu sugerir que a presença desta co-infecção per se não contribui para o aumento das concentrações plasmáticas do fármaco; que, em indivíduos co-infectados com função hepática normal, não há um risco acrescido de toxicidade dependente da concentração e que as indicações para a monitorização terapêutica de efavirenz em indivíduos co-infectados, com função hepática normal, são semelhantes aquelas descritas para indivíduos mono-infectados pelo vírus da imunodeficiência humana. Um outro objectivo específico deste trabalho surgiu quando foi descrito que os efeitos dos análogos não-nucleósidos inibidores da transcriptase reversa no perfil de lípidos e lipoproteínas dos indivíduos pareciam diferir dos efeitos descritos para os inibidores de protease, que eram frequentemente associados a deslipidémia. Os análogos não-nucleósidos inibidores da transcriptase reversa tinham sido associados a aumentos nos níveis de colesterol associado às lipoproteínas de elevada densidade. Esta observação, além de não ser consensual, podia ser imputada ao decréscimo na carga viral dos indivíduos em terapêutica e correspondia a estudos observacionais de curta-duração. Estes factos estimularam a realização de uma análise prospectiva dos valores da concentração de lípidos e lipoproteínas em doentes medicados com efavirenz e à avaliação da sua eventual relação com a concentração deste nti-retroviral, a curto e a longo-termo. Pela primeira vez, foi demonstrado que o efeito do efavirenz no colesterol associado às lipoproteínas de elevada densidade permaneceu durante 36 meses, que o aumento é dependente do valor basal destas lipoproteínas e da concentração plasmática do fármaco. Mostrou-se também que, em associação a este aumento quantitativo, o efavirenz estava associado a um aumento qualitativo, com uma melhoria da função antioxidante destas lipoproteínas, avaliada pela actividade do enzima paraoxonase-1. Em resumo, os diferentes estudos incluídos na presente dissertação têm como conclusão geral que é possível optimizar a resposta à terapêutica com efavirenz através da monitorização das suas concentrações plasmáticas. A realização deste trabalho contribuiu para o conhecimento científico através: 1. Da instalação e validação de um método de quantificação de concentrações de análogos não-nucleósidos inibidores da transcriptase reversa e inibidores da protease em plasma de indivíduos infectados pelo vírus da imunodeficiência humana. 2. Do estudo da variabilidade inter e intra-individual nas concentrações plasmáticas de efavirenz. A superioridade da variabilidade inter-individual relativamente à associada ao mesmo indivíduo comprova a importância de monitorizar as concentrações plasmáticas deste fármaco. 3. Da definição de procedimentos operativos para a monitorização terapêutica do efavirenz em geral e numa população particular: os indivíduos co-infectados pelos vírus da hepatite B e/ou C com função hepática normal. 4. Da descoberta de acções farmacodinâmicas do efavirenz, a longo prazo, nomeadamente o efeito benéfico (quantitativo e qualitativo) no colesterol associado às lipoproteínas de elevada densidade. Este efeito é mantido durante três anos e é dependente da concentração plasmática do fármaco, o que salienta a importância de monitorizar as suas concentrações.

Downstream processing development of enveloped viruses for clinical applications: innovative tools for rational process optimization

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Biotechnology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

O papel dos sistemas de Non-Intrusive Load Monitoring para a eficiência energética do setor residencial

A sustentabilidade energética do planeta é uma preocupação corrente e, neste sentido, a eficiência energética afigura-se como sendo essencial para a redução do consumo em todos os setores de atividade. No que diz respeito ao setor residencial, o indevido comportamento dos utilizadores aliado ao desconhecimento do consumo dos diversos aparelhos, são factores impeditivos para a redução do consumo energético. Uma ferramenta importante, neste sentido, é a monitorização de consumos nomeadamente a monitorização não intrusiva, que apresenta vantagens económicas relativamente à monitorização intrusiva, embora levante alguns desafios na desagregação de cargas. Abordou-se então, neste documento, a temática da monitorização não intrusiva onde se desenvolveu uma ferramenta de desagregação de cargas residenciais, sobretudo de aparelhos que apresentavam elevados consumos. Para isso, monitorizaram-se os consumos agregados de energia elétrica, água e gás de seis habitações do município de Vila Nova de Gaia. Através da incorporação dos vetores de água e gás, a acrescentar ao da energia elétrica, provou-se que a performance do algoritmo de desagregação de aparelhos poderá aumentar, no caso de aparelhos que utilizem simultaneamente energia elétrica e água ou energia elétrica e gás. A eficiência energética é também parte constituinte deste trabalho e, para tal, implementaram-se medidas de eficiência energética para uma das habitações em estudo, de forma a concluir as que exibiam maior potencial de poupança, assim como rápidos períodos de retorno de investimento. De um modo geral, os objetivos propostos foram alcançados e espera-se que num futuro próximo, a monitorização de consumos não intrusiva se apresente como uma solução de referência no que respeita à sustentabilidade energética do setor residencial.