Early detection and screening for urinary tract illnesses is a complex and widespread process which has implications for both preventative care, diagnosis, and treatment monitoring. In this paper, we investigate the use of Raman spectroscopy (RS) for the analysis of urine, a complex biological solution, for the detection of bladder cancer (BCa) and hematuria. Raman spectroscopy is a rapid, low cost, non-destructive analysis method with wide-ranging applicability due to the holistic data capturing nature of the scanning technique. Each Raman scan can be considered a 'snapshot' of the molecular makeup of the sample, and, through proper applications of algorithmic transformation and statistical analysis, many types of assessments can be performed on each sample. In this paper we address creating and utilizing a data pipeline for the purposes of analyzing and characterizing potential samples with hematuria and BCa. The algorithmic transformations utilized include baselining using either the Goldindec or ISREA methods, and intensity normalization. The statistical analysis methods utilized include principal component analysis (PCA), discriminant analysis of principal components (DAPC), analysis of variance (ANOVA), pairwise ANOVA, leave-one-out cross-validation (LOOCV), and partial least squares regression (PLSR). These components of the data pipeline serve to output qualitative or quantitative data, depending on the application. The Rametrix toolbox encompasses the tools required to transform and assess Raman spectra with PCA and DAPC. Using the Rametrix toolbox as well as ANOVA, pairwise ANOVA, and LOOCV, we were able to significantly detect the presence of bladder cancer in a specimen with 80% accuracy. Using the Rametrix toolbox, ANOVA, pairwise ANOVA, LOOCV, and PLSR, we were able to classify samples as pure urine, micro-, or macrohematuria with a greater than 91% accuracy, and quantify the amount of blood in the sample with a high correlation (R-squared value of 0.92). In combination, this style of data pipeline is shown to rapidly and accurately test for multiple symptoms or diseases using similar methodologies. / Master of Science / In the United States, over 37 million people live with chronic kidney disease, over 81 thousand new cases of bladder cancer will be diagnosed, and over 17 thousand people will die from bladder cancer. These serious renal and urinary tract illnesses require urinalysis as a major component of detection, diagnosis, and monitoring of the diseases. This level of required testing has significant costs, both in labor and financial impact. Reduction in both the labor and consumable reagent costs associated with urinalysis would serve to improve the ability for the healthcare system provide the necessary testing for these patients, and reduce the risk of shortages in both reagents and staff. We present a new analysis method, termed 'data pipeline', which would take data from a spectrographic data collection method, Raman Spectroscopy (RS), and generate useable output in the form of classification and quantification. These outputs are highly desired for urinalysis, as urine collection is largely the least invasive testing method related to the urinary tract. As we have shown, the RametrixTM toolbox, an algorithmic package of mathematical methods for assessing spectra, is the backbone of a data pipeline capable of detecting both hematuria, an early warning symptom of many urinary tract illness, and bladder cancer, a notably difficult to detect disease, with high accuracy. This method of analysis is non-destructive of the samples, requires no reagents or single use dipsticks, avoids subjective color assessment, and provides rapid results in a repeatable, potentially automatable manner. We investigate a critical component of this process, the baselining method, in order to further examine and refine the methodology by comparing the accuracy and statistical quality of the results with different baseline methods. It is our goal to implement this methodology with the best component processes, in order to achieve a highly robust, accurate tool for assisting in urinalysis testing.

Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Background New methods to facilitate exploratory analysis in scientific data are in high demand. There is an abundance of available data used only for confirmatory analysis from which new hypotheses can be drawn. To this end, two new exploratory techniques are developed: one for chemometrics and another for visualisation of fundamental scientific experiments. The former transforms large-scale multiple raw HPLC/UV-vis data into a conserved set of putative features - something not often attempted outside of Mass-Spectrometry. The latter method ('StatNet'), applies network techniques to the results of designed experiments to gain new perspective on variable relations. Results The resultant data format from un-targeted chemometric processing was amenable to both chemical and statistical analysis. It proved to have integrity when machine-learning techniques were applied to infer attributes of the experimental set-up. The visualisation techniques were equally successful in generating hypotheses, and were easily extendible to three different types of experimental results. Conclusion The overall aim was to create useful tools for hypothesis generation in a variety of data. This has been largely reached through a combination of novel and existing techniques. It is hoped that the methods here presented are further applied and developed. / AFRIKAANSE OPSOMMING: Agtergrond Nuwe metodes om ondersoekende ontleding in wetenskaplike data te fasiliteer is in groot aanvraag. Daar is 'n oorvloed van beskikbaar data wat slegs gebruik word vir bevestigende ontleding waaruit nuwe hipoteses opgestel kan word. Vir hierdie doel, word twee nuwe ondersoekende tegnieke ontwikkel: een vir chemometrie en 'n ander vir die visualisering van fundamentele wetenskaplike eksperimente. Die eersgenoemde transformeer grootskaalse veelvoudige rou HPLC / UV-vis data in 'n bewaarde stel putatiewe funksies - iets wat nie gereeld buite Massaspektrometrie aangepak word nie. Die laasgenoemde metode ('StatNet') pas netwerktegnieke tot die resultate van ontwerpte eksperimente toe om sodoende ân nuwe perspektief op veranderlike verhoudings te verkry. Resultate Die gevolglike data formaat van die ongeteikende chemometriese verwerking was in 'n formaat wat vatbaar is vir beide chemiese en statistiese analise. Daar is bewys dat dit integriteit gehad het wanneer masjienleertegnieke toegepas is om eienskappe van die eksperimentele opstelling af te lei. Die visualiseringtegnieke was ewe suksesvol in die generering van hipoteses, en ook maklik uitbreibaar na drie verskillende tipes eksperimentele resultate. Samevatting Die hoofdoel was om nuttige middele vir hipotese generasie in 'n verskeidenheid van data te skep. Dit is grootliks bereik deur 'n kombinasie van oorspronklike en bestaande tegnieke. Hopelik sal die metodes wat hier aangebied is verder toegepas en ontwikkel word.

Cleaning validation, in which cleaned surfaces are analysed for residual material, is an important process in pharmaceutical manufacturing and research facilities. Current procedures usually consist of either swab or rinse-water sampling followed by analysis of the samples. The analysis step is typically either rapid but unselective (conductivity, pH, total organic carbon, etc.), or selective but time-consuming (HPLC). This thesis describes the development of an in situ surface-spectroscopic analysis that removes the need for swab sampling and is both rapid and selective. This method has the potential to complement existing analyses to increase the efficiency of cleaning-validation protocols. The spectrometric system consists of a Fourier-transform infrared (FTIR) spectrometer coupled to a fibre-optic grazing-angle reflectance probe, and allows the measurement of infrared reflection-absorbance spectra (IRRAS) from flat surfaces in ~10 s. Multivariate chemometric methods, such as partial least squares (PLS) regression, are used to exploit the high information content of infrared spectra to obtain selective analyses without physical separation of the analyte or analytes from whatever interfering species may be present. Multivariate chemometric models require considerably more effort for calibration and validation than do traditional univariate techniques. This thesis details suitable methods for preparing calibration standards by aerosol deposition, optimising and validating the model by cross- and test-set validation, and estimating the uncertainty by resampling and formula-based approaches. Successful calibration models were demonstrated for residues of acetaminophen, a model active pharmaceutical ingredient (API), on glass surfaces. The root-mean-square error of prediction (RMSEP) was ~0.07 µg cm⁻². Simultaneous calibration for acetaminophen and aspirin, another API, gave a similar RMSEP of 0.06 µg cm⁻² for both compounds, demonstrating the selectivity of the method. These values correspond to detection limits of ~0.2 µg cm⁻², well below the accepted visual detection limit of ~1-4 µg cm⁻². The sensitivity of the method with a stainless steel substrate was found to depend strongly on the surface finish, with highly polished surfaces giving more intense IRRAS. RMSEP values of 0.04- 0.05 µg cm⁻² were obtained for acetaminophen on stainless steel with three different finishes. For this system, severe nonlinearity was encountered for loadings 1.0 µg cm⁻². From the results presented in this thesis, it is clear that IRRAS has potential utility in cleaning validation as a complement to traditional techniques.

Desde as primeiras civilizações, o ser humano se utiliza da diversidade química encontrada na natureza como parte do seu desenvolvimento e até mesmo sobrevivência. Dentre os produtos naturais, as plantas possuem destaque pela quantidade de candidatos a fármacos que chegam à fase final de estudos clínicos. Uma família de plantas de grande interesse é a Asteraceae, cujas plantas biossintetizam diferentes tipos de terpenos, poliacetilenos e substâncias fenólicas. Na busca por novas substâncias ativas, surgem as bibliotecas ou coleções de substâncias, extratos e frações que se tornaram uma das bases para a pesquisa das propriedades químicas e biológicas na indústria. Para a análise e conhecimento dessas bibliotecas são utilizadas técnicas analíticas no estado da arte, como a Cromatografia Líquida de Ultra Eficiência (do inglês, UHPLC), acoplada a Espectrômetros de Massas de Alta Resolução (do inglês, HRMS). Nesse trabalho foi desenvolvido um método analítico em CLAE-EM utilizando a abordagem metabolômica da impressão digital. Esse método foi otimizado utilizando ferramentas in silico e validado segundo padrões internacionais para validação bioanalítica, mostrando-se linear, seletivo, robusto, preciso e acurado para o que foi proposto. Esse método foi utilizado ao longo do processo de otimização para a extração de 244 diferentes espécies de Asteraceae, após a obtenção da melhor condição: 20 mg/mL de droga vegetal, proporção de etanol e água de 80% e tempo de extração de ultrassom de 15 min. A partir dessa condição, foram obtidos os extratos e construída assim a coleção denominada AsterLibII. Cento e vinte substâncias de origem natural isoladas pelo grupo de pesquisa AsterBioChem foram devidamente organizadas para compor a AsterLibI. As estruturas 2D obtidas a partir dessas substâncias, juntamente com mais de 8000 estruturas adicionais obtidas pela conversão de arquivos de levantamento bibliográfico, utilizando ferramentas computacionais, formaram a AsterLibIII. Os dados obtidos pela análise da AsterLibII por UHPLC-HRMS mostram a diversidade dos sinais que representam possíveis substâncias em uma faixa de polaridade de alta a média-baixa, não sendo facilmente interpretadas relações entre as amostras, devido à baixa sensibilidade de gráficos de dispersão e da correlação linear necessária para se obter a redução dimensional efetiva por PCA (Principal Component Analysis). Os modelos matemáticos utilizados tanto para a otimização do método analítico como para a obtenção da melhor condição para as bibliotecas se mostraram estatisticamente significativos e forneceram informações sobre as variáveis. Através das ferramentas analíticas e computacionais utilizadas, foi possível a construção de bibliotecas de produtos naturais promissoras para estudos biológicos e químicos, incluindo estudos voltados para modelos de desreplicação / From the begining, civilizations use the chemical diversity found in nature as part of their growing culture and knowledge, even to overcome disease. Among natural products, plants are most noticed because of their success in reaching the final stage of drug discovery. Asteraceae species are of great interest because of the chemical diversity and their dissemination in nature. The chemical compounds found in Asteraceae are terpenes, flavonoids, coumarins, polyacetylenes, benzofurans and phenylpropanoids. With regard to drug discovery, a new emerging approach is the construction of libraries, collections of extracts, compounds and fractions, which have become a fundamental tool for understanding biological and chemical properties, especially in industry. To perform library analysis towards knowledge, state-of-the-art techniques used are UHPLC and HRMS, mainly coupled. In this work, the development and validation of an analytical methodology using the metabolic fingerprint approach was carried out. After validation, the analytical method was considered linear, precise, robust, accurate and selective for the metabolomics analysis. The analytical method was applied together with response surface studies to obtain an efficient extraction condition that allowed to reach most of the chemical diversity. After that, 244 plant samples were extracted and AsterLibII was constructed. 120 natural compounds isolated by members of the AsterBioChem group were duly organized and became AsterLibI. Then, the 2D structures drawn from AsterLibI, along with about 8000 2D structures extracted and converted by computational means from the bibliographic search, became AsterLibIII. Graphical and mathematical analysis was performed on AsterlibII, although it was not easy to see patterns and continue the investigation of metabolites. This was due to the low sensitivity of the dispersion plots and the expected linear correlation to obtain a real dimensional reduction using Principal Component Analysis (PCA). The mathematical models used to understand the variables in the extraction and development of the method showed statistical significance and they were important to access information. Using analytical and computational tools, it was possible to construct libraries of natural products with great potential for biological and chemical studies, including dereplication studies

Orientador: Rodrigo Sequinel / Coorientador: Danilo Luiz Flumignan / Banca: Kelly Johana Dussan Medina / Banca: Edilene Cristina Ferreira / Banca: Aristeu Gomes Tininis / Banca: Maria Lucia Ribeiro / Resumo: O óleo diesel é o derivado de petróleo mais consumido no Brasil, principalmente no setor de transporte rodoviário, o qual predomina no país, e, por isso, garantir sua qualidade é imprescindível para o funcionamento adequado do motor e redução de emissões veiculares para a atmosfera. Os métodos oficiais de análise demandam bastante tempo e volume de amostra e, em um contexto onde a preocupação ambiental e econômica prevalecem, é interessante o desenvolvimento de metodologias que otimizem os processos, reduzindo tempo de análise e quantidade de amostra e reagentes. Motivado por essa problematização, este trabalho teve como objetivo o desenvolvimento de um método de cromatografia gasosa ultrarrápida com a máxima quantidade de picos cromatográficos possíveis e resolução global satisfatória para correlacionar as áreas destes picos com um banco de dados formado por resultados de ensaios oficiais dos parâmetros físico-químicos, a fim de criar modelos de calibração multivariada por PLS baseados nestas informações. As amostras utilizadas foram de diesel mistura B8 comercial e os parâmetros avaliados foram a massa específica, teor de enxofre, teor de biodiesel, ponto de fulgor e temperaturas de ebulição para amostras 10% destiladas (T10), 50% destiladas (T50), 85% destiladas (T85) e 90% destiladas (T90). Em seis meses, 637 amostras foram selecionadas de forma representativa por HCA e analisadas através do método cromatográfico otimizado, onde a separação cromatográfica ultrarrápida foi... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Diesel fuel is the most consumed petroleum derivative in Brazil, mainly in the road transport sector, which predominates in this country. In this way, guaranteeing its quality is essential for the proper functioning of the engine and the reduction of vehicular emissions to the atmosphere. The official methods of analysis of each characteristic of diesel oil quality require considerable sample time and volume, and in a context where environmental and economic concern prevail, it is interesting to develop methodologies that optimize processes, reducing analysis time, quantity sample and reagents. This work was motived by this problematization and had the objective of developing an ultrafast gas chromatographic method with a maximum amount of chromatographic peaks and a satisfactory global resolution to correlate the areas of these peaks with a database formed by results of official tests of the physicochemical parameters in order to create multivariate calibration models by PLS based on this information. Commercial diesel B8 blend were used as samples and the parameters evaluated were the specific mass, sulfur content, biodiesel content, flash point and boiling temperatures for samples 10% distilled (T10), 50% distilled (T50), 85 % distilled (T85) and 90% distilled (T90). In six months, 637 samples were representatively selected by HCA and analyzed by the optimized chromatographic method, where the ultrafast chromatographic separation was performed in only 6,12 minutes with an ... (Complete abstract click electronic access below) / Doutor

Thesis (MTech (Food Technology))--Cape Peninsula University of Technology, 2018. / The aim of this study was to evaluate the physical, chemical and sensory characteristics of non-alcoholic pearl millet beverage produced using isolated and purified cultures of bioburden lactic acid bacteria (LAB). Traditional non-alcoholic pearl millet beverage (TNAPMB) was produced through spontaneous fermentation. The slurry was fermented for 36 h at 37°C while monitoring the microbial growth at 3 h interval. LAB were grown on deMan, Rogosa and Sharpe agar and identified using Vitek 2 system. The initial numbers of LAB were 7.04 log cfu/ml and increased to 8.00 log cfu/ml after 21 h. The beverage was dominated by LAB and contaminants and their survival was in succession. LAB from the genera Leuconostoc, Pediococcus, Streptococcus and Enterococcus were the main fermenting species in TNAPMB. Pearl millet extract (PME) was produced by hydrating pearl millet flour (PMF) with water (1:10, PMF:Water). To the mixture sprouted rice flour (10%), ground ginger (10%) and pectin (0.6%) were added. Stable PME was used in the production of plain non-alcoholic pearl millet beverage (PNAPMB). PME was pasteurized at 98°C for 30 min, hot filled and cooled to 25°C. The fluid was inoculated with Leuconostoc mesenteroides, Pediococcus pentosaceus and Enterococcus gallinarum each at 0.05, 0.075 and 0.1%, respectively, using factorial design and fermented for 18 h at 37°C. The pH of the beverage ranged between pH 3.32 and pH 3.90. L. mesenteroides, P. pentosaceus, E. gallinarum, the interaction between L. mesenteroides and P. pentosaceus and the interaction between L. mesentoroides and E. gallinarum had a significant effect (p ˂ 0.05) on the pH of PNAPMB except the interaction between P. pentosaceus and E. gallinarum (p = 0.631). The total titratable acidity (TTA) of the beverage ranged from 0.50 to 0.72%. All cultures had a significant influence (p ˂ 0.05) on the TTA of the beverage with the exception of the interaction between L. mesenteroides and E. gallinarum (p = 0.102). However, Monte Carlo simulation showed that E. gallinarum caused an increase in the pH and a decrease in the TTA of the beverage. During fermentation, the pH of the beverage is desired to decrease while the TTA increases, hence E. gallinarum was removed. The interaction between L. mesenteroides and P. pentosaceus at 0.05% and 0.025%, respectively produced an acceptable PNAPMB with potential for commercialization. Furthermore, moringa supplemented non-alcoholic pearl millet beverage (MSNAPMB) was produced by adding 4% of moringa (Moringa oleifera) leaf powder extract during the production of PNAPMB. The physicochemical, nutritional, microbial (LAB) and sensory characteristics of the PNAPMB, MSNAPMB and TNAPMB were determined. LAB were significantly (p < 0.05) affected by the fermentation period and increased from 3.32 to 7.97 log cfu/ml and 3.58 to 8.38 log cfu/ml in PNAPMB and SNAPMB, respectively. The pH of PNAPMB decreased from pH 5.05 to pH 4.14 while the pH of MSNAPMB decreased from pH 5.05 to pH 3.65 during the 18 h fermentation. The growth of LAB during fermentation had a significant effect (p < 0.05) on the pH of the beverages. The TTA increased from 0.14 to 0.22% and increased from 0.17 to 0.38%, in PNAPMB and MSNAPMB, respectively. The TTA of the beverage was affected significantly (p < 0.05) by the 18 h of fermentation. The protein content was 1.62, 2.17 and 1.50% in PNAPMB, MSNAPMB and TNAPMB, respectively. PNAPMB sample was deemed acceptable in comparison to the MSNAPMB. The total colour difference (ΔE) was 5.91 and 10.60 in PNAPMB and MSNAPMB, respectively in comparison to the TNAPMB. Volatile compounds with beneficial effect such as anti-inflammatory and anti-pathogenic properties were identified in the beverages. Principal component analysis indicated that the variations in characteristics of PNAPMB and MSNAPMB could be explained using total fat, saturated fat, total sugar, ash, moisture, proteins, chroma (C), hue and b*. The results showed that isolated pure cultures could be used as starter cultures in the production of non-alcoholic cereal beverages at a commercial level with predictable quality and safety properties.

Há na literatura um grande número de publicações versando sobre métodos analíticos para a determinação de razões isotópicas através das mais diversas modalidades de espectrometria. Entretanto, praticamente todos esses métodos possuem umarestrição comum em relação à gama de íons moleculares que podem ser utilizados nessas determinações: eles devem ser, ou íons elementares, ou íons cujo único átomo poli-isotópicoé o elemento de interesse. Isto é obtido, ou mediante adestruição das moléculas da amostra, ou complexos tratamentosquímicos para a obtenção de espécies poli-atômicas adequadas.Neste trabalho, foi desenvolvido um método matemático capazde deconvolver o padrão isotopomérico de um íon molecular,isto é, calcular os padrões isotópicos dos átomos que ocompõem dados a sua fórmula elementar e o seu espectro .A principal contribuição de um método desse tipo é a ampliaçãoda variedade de espécies químicas e modalidades de espectrometria aceitáveis para análises isotópicas. O algoritmo desenvolvidofoi caracterizado através da sua aplicação a um grande númerode espectros simulados visando modelar a resposta do métodoquando submetido a algumas imperfeições experimentais típicasde espectrometria e relevantes para análises isotópicas,tais como ruído, discriminação instrumental de massas, nãolinearidade de detecção, falta de resolução e má compensaçãode espectral. Os resultados obtidos permitiram concluirque, ao contrário do que o senso comum às vezes possa sugerir,determinações isotópicas realizadas através de espéciespoli-atômicas podem, muitas vezes, ser mais exatas e precisasque as efetuadas pelas abordagens convencionais. Concluiu-seque, de maneira geral, os resultados tendem a ser tantomelhores quanto maior for o número de instâncias do elementode interesse na fórmula do íon molecular escolhido. Foiestudada experimentalmente a viabilidade de métodos analíticosde equilibração para determinações de razões isotópicashidrogênio/deutério em amostras aquosas utilizando polióiscomo sondas e espectrometria com ionização electrospray.Os polióis testados foram o manitol, o ácido glucônico,a glucosamina e a N-metilglucamina (através do seu complexocom o ácido bórico). Os resultados obtidos mostraram algunsdesvios sistemáticos que sugerem que haja troca parcialde hidrogênios não lábeis dos polióis na fase gasosa, oque impossibilitaria esta aplicação. Sondas aternativasaos polióis são propostas. / Several articles can be found in the literature describing methods forthe determination of isotopic ratios through the various modalities ofmass spectrometry. However, almost all of them have a commonrestriction on the type of molecular ion that can be employed in thesedeterminations: they must be either elemental ions, or polyatomic ionswhose sole polyisotopic element is the one being analysed. This isusually achieved through the destruction of the molecules, or throughcomplex synthetic procedures. In this work, a mathematical methodcapable of deconvolving the isotopomeric pattern of a molecular ion,i.e., calculating the isotopic pattern of its constituent atoms givenits formula and its mass spectrum, has been developed. The maincontribution of such a method to the field is the broadening of therange of acceptable chemical species for isotopic analyses. Thedeveloped algorithm was characterized by applying it to a large numberof simulated spectra with the objective of modelling its response tosome experimental imperfections common to mass spectrometry andrelevant for isotopic analyses, such as noise, instrumental massdiscrimination, detection non-linearity, lack of resolution and badbaseline compensation. The results allowed us to conclude that, inspite of whatever commonsense might suggest, isotopic analysescarried out through the polyatomic approaches can, in many cases, bemore exact and precise than those performed through conventionalapproaches. It could also be concluded that, in general, the largerthe number of instances of the element of interest in the formula ofthe chosen ion, the better the results become. Also as part of theproject, the viability of employing polyols as probes for thehydrogen/deuterium ratio in aquous samples in equilibration methodsand electrospray mass spectrometry has been studied. The studiedpolyols were: manitol, gluconic acid, glucosamine and N-metilglucamine(through its complex with boric acid). The obtained results showedsome systematic errors that suggest that there might be a partialexchange of non-labile hydrogen atoms during the electrosprayphenomenon. Alternative probes are proposed.

Com o intuito de contribuir para a tipificação da aguardente paulista, 35 analitos foram analisados em 107 amostras coletadas no Estado de São Paulo no momento da sua destilação. Os resultados analíticos foram avaliados utilizando-se análise multivariada (quimiometria). A quimiometria foi utilizada para definir os melhores discriminantes químicos em cada tipo de análise. Na distinção entre a aguardente destilada em alambique e a aguardente destilada em coluna, as análise exploratórias (PCA, HCA e PLS) demonstraram que existe um distinção entre estes dois grupos de bebidas. Os modelos estatísticos criados utilizando-se das análises de LDA e CDA apresentaram uma porcentagem de acerto superior a 95,0% na distinção entre estes dois grupos de bebidas. Quando considerado, na análise exploratória, três grupos de bebidas (alambiques típicos, colunas típicas e alambiques mistos, esta apresentou bons resultados apenas nas análises de PCA e HCA. Não foi criado modelo estatístico considerando três grupos de bebidas. Na última etapa deste trabalho, foi realizada uma análise exploratória (PCA e HCA) nas 107 amostras coletadas no Estado de São Paulo, sem considerar o processo de destilação. Foram encontrados diferentes agrupamentos considerando as características químicas de todas as amostras. No entanto, a correlação definitiva entre estes grupos e as características regionais do Estado de São Paulo não foi observada. / Aiming at achieving typification of the paulista sugar-cane spirits, 35 compounds were analyzed in 107 samples collected in the State of São Paulo at the moment of distillation. The analytical results were obtained through multivariate analysis (chemometric), which was used to determine the best chemical discriminates in each type of the statistical analysis. Exploratory analyses (PCA, HCA and PLS) showed a distinction between the sugar-cane spirits distilled in stills and the ones distilled in continuous columns. After conducting LDA and CDA analyses, the resulting statistical models revealed a significantly high probability (95,0%) to correctly identify the system of distillation used in the process. Exploratory analyses performed in typical stills, typical columns and mixed stills showed good results for PCA and HCA only. No statistical models considering the three groups of drinks were created. The last phase of the present study involved exploratory analyses (PCA and HCA) performed in the 107 samples collected in the State of São Paulo. Considering the chemical characteristics of all samples, different groupings were found. However, a definitive correlation among these groups with the production areas in the State of São Paulo was not observed.

O câncer é uma doença que aflige pessoas no mundo todo, e mata muitas todos os anos. Muitos estudos são desenvolvidos para sintetizar novos compostos com atividade antitumoral cada vez melhor. O maior número de compostos possibilita um maior número de possibilidades de cura, já que alguns tumores podem adquirir resistência ao medicamento, sendo necessária a troca por outro.<br /> Para que não seja feita uma síntese aleatória de compostos, desperdiçando tempo, reagentes e dinheiro sintetizando compostos inativos, um estudo teórico prévio para orientar a síntese é válido. Um estudo QSAR pode orientar a síntese indicando quais compostos são mais interessantes de serem sintetizados e quais são menos interessantes. Assim, há o desenvolvimento de mais compostos ativos em um menor tempo, do que se fosse realizada sínteses e testes para todos os compostos possíveis.<br /> O presente estudo tem esse foco, avaliar a relação quantitativa entre a estrutura molecular e a atividade antitumoral de compostos &beta;-carbolínicos substituídos nas posições 1 e 3. Nesse estudo será possível elucidar quais características são relevantes para que os compostos sejam ativos no tratamento de câncer de pulmão e melanoma. / Cancer is a disease that afflicts people worldwide and kills many every year. Many studies are developed to synthesize new compounds with better antitumor activity. The largest number of compounds allows a greater number of curability, because some tumors may acquire used drug resistance and are necessary different drugs.<br /> To avoid a random synthesis of compounds, wasting time, money and reagents in synthesizing inactive compounds, a previous theoretical study as guide of synthesis is valid. A QSAR study can guide the synthesis indicating which compounds are most interesting to be synthesized and which are less interesting. Thus, more compounds active are developed in a shorter time.<br /> The present study has this focus, assess the quantitative relationship between molecular structure and antitumor activity of &beta;-carboline compounds substituted in positions 1 and 3. In this study will be possible to elucidate characteristics that are relevant to the compounds under study be active in the treatment of lung cancer and melanoma.

Orientadora: Maria Valnice Boldrin Zanoni / Banca: Hideko Yamanaka / Banca: Sonia Maria Alves Jorge / Banca: Leonardo Lataro Paim / Banca: Silvia Helena Pires Serrano / Banca: Magno Aparecido Gonçalves Trindade / Resumo: A aplicabilidade dos métodos analíticos na Química Forense tem como grande desafio a complexidade das matrizes biológicas (urina, fezes, suor, cabelos e pelos), o uso de técnicas com baixo limite de detecção, a avaliação de metabólitos gerados em baixa concentração após metabolização e a busca de técnicas e metodologias eficientes, porém de baixo custo. O objetivo do presente trabaho foi investigar novos métodos eletroanalíticos para determinação dos diuréticos bumetanida (BMT), hidroclorotiazida (HCT) e triantereno (TRT) em consonância com as diretrizes e controle da Agência Mundial Antidopagem. Sensores eletroquímicos foram desenvolvidos usando eletrodos compósitos, eletrodos de carbono vítreo e eletrodo de nanotubos de TiO2 tratados catodicamente modificados com partículas magnéticas, óxido de grafeno reduzido e nanotubos de carbono multiparedes para a determinação dos diuréticos BMT, HCT e TRT, proibidos pela Agência Mundial Antidoping (WADA). Para a determinação do diurético TRT foi desenvolvido um sensor baseado na modificação da superfície de um eletrodo compósito grafite-epoxy com partículas magnéticas funcionalizadas com grupo tosil. Após otimização multivariada dos parâmentros inerentes à técnica de voltametria de onda quadrada, uma curva de calibração foi construída no intervalo de 0,500 a 99,8 µmol L−1 com limite de detecção de 1,47×10−7 mol L−1. O sensor foi aplicado em amostra de urina e comparado com a técnica de LC-MS/MS onde não houve diferença significativa ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The applicability of the analytical methods in Forensic Chemistry has as a great challenge the complexity of the biological matrices (urine, feces, sweat, hair and hair), the use of techniques with low limit of detection, the evaluation of metabolites generated in low concentration after metabolism and the search for efficient but cost-effective techniques and methodologies. The objective of the present study was to investigate new electroanalytical methods for the determination of diuretics bumetanide (BMT), hydrochlorothiazide (HCT) and trianterene (TRT) in accordance with the guidelines and control of the World Anti-Doping Agency. Electrochemical sensors were developed using composite electrodes, glassy carbon electrodes and self-doping TiO2 nanotube electrodes modified with magnetic particles, reduced graphene oxide and carbon nanotubes for the determination of the diuretics BMT, HCT and TRT banned by the World Anti-Doping Agency (WADA). For the determination of the diuretic TRT, a sensor based on the modification of the surface of a composite graphite-epoxy electrode with magnetic particles functionalized with tosyl group was developed. After a multivariate optimization of the parameters inherent to the square wave voltammetry technique, a calibration curve was constructed in the range of 0.500 to 99.8 μmol L−1 with a detection limit of 1.47×10−7 mol L−1. The sensor was applied in a urine sample and compared to the LC-MS/MS technique where there was no significant differ... (Complete abstract click electronic access below) / Doutor