Charge detection mass spectrometry (CDMS) is a single particle technique capable of simultaneously measuring charge and mass-to-charge ratios for individual ions or particles. The linear array CDMS design theoretically has no upper mass limit and is therefore a choice method for the analysis of high mass and heterogeneous samples, such as dust microparticles in the Martian atmosphere. This dissertation describes the development of a novel charge detection mass spectrometer made of printed circuit boards (PCB) for the analysis of dust microparticles in the Martian atmosphere. Development of this device has required investigations in analysis methods and the engineering design of both the PCB device and the vacuum chamber system used in laboratory experiments. Accurate velocity analysis is crucial in determining correct particle mass in linear array CDMS. By combining the Shockley-Ramo theorem–which allows for the calculation of instantaneous image current for a system of electrodes when a point charge passes them–and SIMION ion optics simulations effective electrode length can be determined for any given charge detector geometry and aid in charge detector engineering and design process. Applying these simulation results to experimental data yields velocity agreement for a PCB charge detector within 0.44% RSD. The novel PCB CDMS device was demonstrated for the analysis of multiple types of microparticles of varying size and charge similar to that expected of atmospheric Mars dust. This device is able to measure particle charge above 1,500 elementary charges of either polarity. Simulations show that for microparticles having a size and density close to that which is expected for Mars dust, the device is able to ideally measure the mass of particles ranging from 0.2–2.5 μm in diameter, providing broad coverage of particles too small to be observed by optical scattering and other techniques that have been previously used on Mars.

O câncer de mama é um dos maiores problemas de saúde para a população feminina, devendo ser encarado como um importante problema de saúde pública. A ultrassonografia é considerada o método mais efetivo na complementação de diagnóstico de doenças mamárias, porém a forma de aquisição desse método diagnóstico degrada a imagem sob diversas formas, destacando-se o ruído speckle, o qual deixa a imagem com aspecto granulado, dificultando assim a separabilidade entre os objetos da cena. Este trabalho apresenta uma técnica automática para segmentação de nódulos mamários em imagens de ultrassom. O algoritmo permite a extração das bordas nodulares, permitindo assim a obtenção de parâmetros clínicos utilizados no diagnóstico mamário. Todo o processo se baseia em três etapas: minimização do ruído speckle, aumento de contraste da imagem e por fim, a segmentação. A técnica utilizada para minimização do ruído speckle baseia-se na Wavelet da família Symlet; técnicas para aumento de contraste na imagem são aplicadas para a segmentação. A partir daí, é aplicado o algoritmo de segmentação Asterisco, originalmente proposto para a detecção de microcalcificações em mamografias por raios X, e que mostrou também eficiência para os objetivos deste trabalho. A técnica Asterisco em conjunto com as de pré-processamento (minimização de ruído e aumento de contraste) produziu taxa de sensibilidade na detecção de nódulos da ordem de 90%. Em relação à qualidade da segmentação, a técnica apresentada neste trabalho também se mostrou satisfatória, superior às técnicas testadas, de acordo com a análise feita pelo cálculo de coeficientes de correlação de Pearson. É possível concluir que o sistema desenvolvido neste trabalho pode constituir-se numa ferramenta eficaz de segmentação de nódulos mamários em imagens de ultrassom, auxiliando o conjunto de informações disponíveis para um classificador automático em esquemas CAD em mamografia. / Breast cancer is one of the main health problems of the female population and should be faced as an important public health care issue. The ultrasound scanning is considered the most effective in complementary method of breast diagnosis. Nevertheless, the acquisition format of this sort degrades the images in various ways, being the speckle noise of noticeably influence once it leaves the image with grainy aspect. Therefore, the separability between objects of the scene is hindered. This work presents an automatic technique of ultrasound image segmentation of breast lumps. The algorithm allows the extraction of the nodular edges permitting the clinical parameters to be obtained for the breast diagnosis. All the process is based on three steps: speckle noise minimization, image contrast intensification and finally the segmentation. The technique used on the speckle noise minimization is based on the Wavelet transform of the Symlet family; image contrast intensifications are applied for the segmentation. Thereafter the algorithm of segmentation Asterisco is applied, which is originally proposed to detect micro calcifications in X-ray mammography, and has also shown efficiency regarding the goals of the present work. The Asterisco technique along with the pre processing techniques (noise minimizing and contrast intensification) produced sensitivity rate in nodule detection by 90%. With regard to the segmentation quality, the presented technique has also proved to be satisfactory as it has superior quality to the ones tested according to the analysis made by the Pearson\'s correlation coefficients calculation. Thus, it is possible to conclude that the system, which has been developed in this work, can constitute an efficient breast lumps segmentation tool so as to aid the set of available information to an automatic classifier in mammography CAD schemes.

O câncer de mama é um dos maiores problemas de saúde para a população feminina, devendo ser encarado como um importante problema de saúde pública. A ultrassonografia é considerada o método mais efetivo na complementação de diagnóstico de doenças mamárias, porém a forma de aquisição desse método diagnóstico degrada a imagem sob diversas formas, destacando-se o ruído speckle, o qual deixa a imagem com aspecto granulado, dificultando assim a separabilidade entre os objetos da cena. Este trabalho apresenta uma técnica automática para segmentação de nódulos mamários em imagens de ultrassom. O algoritmo permite a extração das bordas nodulares, permitindo assim a obtenção de parâmetros clínicos utilizados no diagnóstico mamário. Todo o processo se baseia em três etapas: minimização do ruído speckle, aumento de contraste da imagem e por fim, a segmentação. A técnica utilizada para minimização do ruído speckle baseia-se na Wavelet da família Symlet; técnicas para aumento de contraste na imagem são aplicadas para a segmentação. A partir daí, é aplicado o algoritmo de segmentação Asterisco, originalmente proposto para a detecção de microcalcificações em mamografias por raios X, e que mostrou também eficiência para os objetivos deste trabalho. A técnica Asterisco em conjunto com as de pré-processamento (minimização de ruído e aumento de contraste) produziu taxa de sensibilidade na detecção de nódulos da ordem de 90%. Em relação à qualidade da segmentação, a técnica apresentada neste trabalho também se mostrou satisfatória, superior às técnicas testadas, de acordo com a análise feita pelo cálculo de coeficientes de correlação de Pearson. É possível concluir que o sistema desenvolvido neste trabalho pode constituir-se numa ferramenta eficaz de segmentação de nódulos mamários em imagens de ultrassom, auxiliando o conjunto de informações disponíveis para um classificador automático em esquemas CAD em mamografia. / Breast cancer is one of the main health problems of the female population and should be faced as an important public health care issue. The ultrasound scanning is considered the most effective in complementary method of breast diagnosis. Nevertheless, the acquisition format of this sort degrades the images in various ways, being the speckle noise of noticeably influence once it leaves the image with grainy aspect. Therefore, the separability between objects of the scene is hindered. This work presents an automatic technique of ultrasound image segmentation of breast lumps. The algorithm allows the extraction of the nodular edges permitting the clinical parameters to be obtained for the breast diagnosis. All the process is based on three steps: speckle noise minimization, image contrast intensification and finally the segmentation. The technique used on the speckle noise minimization is based on the Wavelet transform of the Symlet family; image contrast intensifications are applied for the segmentation. Thereafter the algorithm of segmentation Asterisco is applied, which is originally proposed to detect micro calcifications in X-ray mammography, and has also shown efficiency regarding the goals of the present work. The Asterisco technique along with the pre processing techniques (noise minimizing and contrast intensification) produced sensitivity rate in nodule detection by 90%. With regard to the segmentation quality, the presented technique has also proved to be satisfactory as it has superior quality to the ones tested according to the analysis made by the Pearson\'s correlation coefficients calculation. Thus, it is possible to conclude that the system, which has been developed in this work, can constitute an efficient breast lumps segmentation tool so as to aid the set of available information to an automatic classifier in mammography CAD schemes.

La spectrométrie de masse est devenue un outil indispensable pour la recherche en protéomique, notamment grâce au développement récent de nouveaux spectromètres de masse comme l’Orbitrap et de nouvelles méthodes de dissociation. La stratégie « bottom-up » (analyse des mélanges de peptides protéolytiques) est la plus utilisée par son efficacement et sa simplicité par rapport à la stratégie top-down (analyse des peptides plus longs ou des protéines intactes), mais cette dernière permet une caractérisation plus complète des isoformes de protéines et des modifications post-traductionnelles.Les méthodes de dissociation utilisant des photons, comme la photodissociation dans le domaine ultra-violet (UVPD) et la dissociation multiphotonique infrarouge (IRMPD), ont reçu une grande attention comme approches alternatives aux méthodes de dissociation par collision. L'absorption du photon UV à haute énergie peut être « diluée » sur l'ensemble du peptide ou de la protéine et provoque une fragmentation étendue du squelette peptidique (liaisons C-C), tandis que les photons IR à faible énergie augmentent progressivement l'énergie interne et dissocient préférentiellement les liaisons amide (C-N) les plus labiles.Cette thèse est centrée sur le développement de méthodes et les applications pour une caractérisation structurale de biomolécules par des méthodes d'activation utilisant des photons. L'intérêt de combiner des photons infrarouges à faible énergie et des photons UV à haute énergie dans un spectromètre de masse Orbitrap, pour la caractérisation de petites protéines, a été évalué. En outre, la dissociation infrarouge multiphotonique a été implémentée dans un piège à ions électrostatique afin d’étendre les méthodes de fragmentation aux macromolécules de très haut poids moléculaires dans le domaine mégadalton. L'une des principales avancées de cette thèse a été d'adapter ces méthodes de spectrométrie de masse aux objets biomoléculaires, allant des petits peptides (dans la gamme de masse de kilodalton) à des fibres de protéines entières (dans la gamme de masse de mégadalton) / The structural characterization of proteins often required them to be fragmented into small units containing only few amino acids. In bottom-up approach, proteins are cleaved into small peptides by enzyme then these peptides are subjected to further fragmentation in a collision cell of a tandem mass spectrometer. However, in top-down approach, proteins can directly be dissociated (without enzyme) into small fragments by collision, electron and photon-driven dissociations. Photon-based activation methods including ultraviolet photodissociation (UVPD) and infrared multiphoton dissociation (IRMPD) have received great attention as an alternative to electron-driven and collision induced dissociation methods. Absorption of the high-energy UV photon is dispersed over the whole peptide or protein and stimulates extensive C?Ca backbone fragmentation while the low-energy IR photons gradually increases the internal energy and thus favorably dissociates the most labile amide (C?N) bonds. This thesis focuses on the method development and applications for characterizing biomolecules by photon-based activation methods. The interest of combining high-energy UV photons and low-energy IR photons in an Orbitrap mass spectrometer, for protein and post-translationally modified peptide characterization, has been evaluated. Moreover, infrared multiphoton dissociation has been implemented in a gated electrostatic ion trap to push forward the limit of fragmentation methods to large megadalton ions. One of the main breakthroughs in this thesis is the ability to adapt these method developments and applications to biomolecular objects ranging from small peptides (in kilodalton mass range) to entire protein fibrils (in megadalton mass range)

One of the most relevant group of toxicologically significant compounds in beer are N-nitrosamines. In this thesis, the attention was paid especially on non-volatile nitroso compounds whose concentrations in beer, a chemical structure, and a biological effect has not been known yet. For the reason of the lack of knowledge regarding this compound group, the method for their sensitive detection by chemiluminescence detection after gas chromatographic separation was developed. This method permits a classification of detected nitroso compounds to different groups (N-nitroso, C-nitroso, and combination of C-nitroso and nitro) and distinguish them from interferences. The method is based on recording of a pyrolytic profile of each chromatographic peak, the profiles are then processed by discriminant analysis. The method has been developed for finding and structural identification purposes of these unknown compounds. Its application on an artificially nitrosated beer sample, together with gas chromatographic tandem mass spectrometric analysis, led to structural identification of several representatives of nitroso compounds. Sensory active compounds in this thesis are represented by carbonyl compounds and fatty acids. Carbonyl compounds - furfural and hydroxymethylfurfural - were used during the development...