27 resultados para Drug-excipient interaction
em Universidade do Minho
Resumo:
Oceans are a vast source of natural substances. In them, we find various compounds with wide biotechnological and biomedical applicabilities. The exploitation of the sea as a renewable source of biocompounds can have a positive impact on the development of new systems and devices for biomedical applications. Marine polysaccharides are among the most abundant materials in the seas, which contributes to a decrease of the extraction costs, besides their solubility behavior in aqueous solvents and extraction media, and their interaction with other biocompounds. Polysaccharides such as alginate, carrageenan and fucoidan can be extracted from algae, whereas chitosan and hyaluronan can be obtained from animal sources. Most marine polysaccharides have important biological properties such as biocompatibility, biodegradability, and anti-inflammatory activity, as well as adhesive and antimicrobial actions. Moreover, they can be modified in order to allow processing them into various shapes and sizes and may exhibit response dependence to external stimuli, such as pH and temperature. Due to these properties, these biomaterials have been studied as raw material for the construction of carrier devices for drugs, including particles, capsules and hydrogels. The devices are designed to achieve a controlled release of therapeutic agents in an attempt to fight against serious diseases, and to be used in advanced therapies, such as gene delivery or regenerative medicine.
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The aim of this study is evaluating the interaction between several base pen grade asphalt binders (35/50, 50/70, 70/100, 160/220) and two different plastic wastes (EVA and HDPE), for a set of new polymer modified binders produced with different amounts of both plastic wastes. After analysing the results obtained for the several polymer modified binders evaluated in this study, including a commercial modified binder, it can be concluded that the new PMBs produced with the base bitumen 70/100 and 5% of each plastic waste (HDPE or EVA) results in binders with very good performance, similar to that of the commercial modified binder.
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Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.
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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
Resumo:
Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.
Resumo:
Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.
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Efficient liposome disruption inside the cells is a key for success with any type of drug delivery system. The efficacy of drug delivery is currently evaluated by direct visualization of labeled liposomes internalized by cells, not addressing objectively the release and distribution of the drug. Here, we propose a novel method to easily assess liposome disruption and drug release into the cytoplasm. We propose the encapsulation of the cationic dye Hoechst 34,580 to detect an increase in blue fluorescence due to its specific binding to negatively charged DNA. For that, the dye needs to be released inside the cell and translocated to the nucleus. The present approach correlates the intensity of detected fluorescent dye with liposome disruption and consequently assesses drug delivery within the cells.
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The use of buffers to maintain the pH within a desired range is a very common practice in chemical, biochemical and biological studies. Among them, zwitterionic N-substituted aminosulfonic acids, usually known as Good's buffers, although widely used, can complex metals and interact with biological systems. The present work reviews, discusses and updates the metal complexation characteristics of thirty one commercially available buffers. In addition, their impact on biological systems is also presented. The influences of these buffers on the results obtained in biological, biochemical and environmental studies, with special focus on their interaction with metal ions, are highlighted and critically reviewed. Using chemical speciation simulations, based on the current knowledge of the metal-buffer stability constants, a proposal of the most adequate buffer to employ for a given metal ion is presented.
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Poly(vinylidene fluoride-trifluoroethylene)/NaY zeolite composite membranes were prepared by solvent casting and evaluated as a suitable drug release platform through the evaluation of loading and release of ibuprofen. The membranes were characterized at the morphological, structural and mechanical levels. The 1H-NMR spectra indicate that only the membranes with 16 and 32 % of NaY were useful for IBU encapsulation and the drug release was followed by UV-Vis spectroscopy. The release profile is independent of the zeolite content and can be described by the Korsmeyer-Peppas model. The membrane with 32 % zeolite content releases more than double IBU amount when compared with the membrane with 16 % showing that zeolite content allows tailoring membrane drug release content for specific applications. The drug release platform developed in this work is suitable for other drugs and applications.
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The identification of new and druggable targets in bacteria is a critical endeavour in pharmaceutical research of novel antibiotics to fight infectious agents. The rapid emergence of resistant bacteria makes today's antibiotics more and more ineffective, consequently increasing the need for new pharmacological targets and novel classes of antibacterial drugs. A new model that combines the singular value decomposition technique with biological filters comprised of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of E. coli has been developed to predict potential drug targets in the Enterobacteriaceae family [1]. This model identified 99 potential target proteins amongst the studied bacterial family, exhibiting eight different functions that suggest that the disruption of the activities of these proteins is critical for cells. Out of these candidates, one was selected for target confirmation. To find target modulators, receptor-based pharmacophore hypotheses were built and used in the screening of a virtual library of compounds. Postscreening filters were based on physicochemical and topological similarity to known Gram-negative antibiotics and applied to the retrieved compounds. Screening hits passing all filters were docked into the proteins catalytic groove and 15 of the most promising compounds were purchased from their chemical vendors to be experimentally tested in vitro. To the best of our knowledge, this is the first attempt to rationalize the search of compounds to probe the relevance of this candidate as a new pharmacological target.
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O presente artigo tem por objetivo validar uma versão adaptada do Partner Interaction Questionnaire (PIQ), instrumento que avalia o suporte para deixar de fumar dado pelo parceiro. É apresentada uma versão adaptada do PIQ para fumantes e abstinentes. Participaram no estudo 224 fumantes (52.7% do sexo feminino e 47.3% do sexo masculino; média de idades=28.6 anos; DP=8.69) e 169 ex-fumantes (68.6% do sexo masculino e 31.4% do sexo feminino; média de idades= 43.1 anos; DP=13.02). O instrumento apresentou boa fidelidade (alfa de Cronbach: 0.73) para a subescala positiva e para a subescala negativa (alfa de Cronbach: 0.77). O estudo de validade revelou a presença de dois fatores que explicam 43.36% da variância. O instrumento apresenta boa validade de construto, correlacionando-se positivamente com o ajustamento de casais e a qualidade de vida mental, e negativamente com a depressão. Esta versão adaptada do PIQ reuniu as condições necessárias para a sua aplicação em fumantes e ex-fumantes, podendo ser uma escala útil em programas de intervenção de cessação tabágica e de manutenção da abstinência.
Resumo:
[Extrat] The advent of thc internet raised questions about the role of radio in a fast-changing media environment. Many voices forecast its end but in the summer of 2008 the Swedish Radio and TV Authority published a study named 'The Future of Radio', which clearly opposed the pessimism of recent analysis. While the study anticipates the exhaustion of the FM model, it clearly broadens perspectives for DAB and internet radio, highlighting digitalization as the key element for the future relevance of radio. The Portuguese researcher and radio professional João Paulo Meneses states that 'the future of radio relies upon the internet', calling the broad service offerings of the net the pathway for the survival of radio from the threats to its two essential aspects: rnobility and accumulation (Meneses 2008). Accumulation is radio's capability to be used in a nonexclusive manner, which means that a listener can use the radio while performing other activities, like cooking, sewing, reading, writing or jogging.
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Dissertação de mestrado em Genética Molecular
Resumo:
Zeolites Y (faujasite) and MOR (mordonite) were used as hosts for temozolomide (TMZ), a current good-standard chemotherapeutic agent used in the treatment of glioblastoma brain tumors. TMZ was loaded into zeolites by liquid-phase adsorption at controlled pH. FTIR, 1H NMR, MS, SEM, UV/vis and chemical analysis demonstrated the successful loading of TMZ into zeolite hosts. The hydrolysis of TMZ in MTIC (TMZ metabolite) after the preparation of drug delivery systems (DDS) was observed in simulated body fluid. The effect of zeolites and DDS were evaluated on the viability of glioblastoma cell lines. Unloaded Y zeolite presented toxicity to cancer cells in contrast to MOR. In accordance, the best results in potentiation of the TMZ effect was obtained with MOR. We found that mordonite loaded with 0.026 mmol of TMZ was able to decrease the half maximal inhibitory concentrations (IC50) at least 3-fold in comparison to free temozolomide both in vitro and in vivo.
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Tese de Doutoramento em Engenharia de Eletrónica e de Computadores