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

O alquil benzeno sulfonato linear (LAS) é o principal tensoativo aniônico, largamente utilizado em detergentes. O alquil benzeno linear (LAB), um subproduto, faz uma associação ao tensoativo devido a sulfonação incompleto do LAS. Recentemente tem tido grande interesse de usá-lo como marcador de efluente doméstico no ambiente aquático. Neste estudo, um novo método para determinação de LAB em detergentes envolvendo cromatografia a gás acoplado a espectrometria de massa em combinação com microextração em fase sólida (SPME) é proposto. O planejamento fatorial foi utilizado para obter valores ótimos para os principais parâmetros de análises de LAB em detergentes usando SPME direto como etapa de pré-concentração. SPME-GC/MS combinada com análise de componentes principais (PCA) e empregada para avaliar os parâmetros que afetam a SPME. O método otimizado foi aplicado nas amostras de detergentes comerciais (0,97 a 3,67 mg.g-1 LAB totais) e LAS (24,7 mg.g-1 LAB totais). Um perfil similar foi encontrado entre as amostras de detergentes e o LAS indicando que os tensoativos são idênticos. E algumas amostras, os LAB não foram encontrados (limite de detecção < 0,2 µg.mL-1). / Linear Alkylbenzene Sulfonated (LAS) is the main anionic surfactant, wide used in detergents. The Linear Alkylbenzene (LAB), a by-product, makes association with the surfactant, due the incomplete sulfonation of the LAS. Recently there has been widespread interest in their use as markers tracers of domestic waste in the aquatic environment. In this study, a new method for determination of LAB in detergents involving gas chromatography coupled to mass spectrometry (GC-MS) in combination with Solid Phase Microextraction (SPME) is proposed. A factorial design was utilized to obtain the optimum values for the main operation parameters in the analysis of LAB in detergents using direct SPME in the pre-concentration step. SPME-GC/MS in combination whit principal component analysis (PCA) was employed to evaluate the parameters that affect on SPME. The optimized method was applied to commercial detergents (0.97 and 3.67 mg.g-1 of total LAB) and LAS ( 24.47 mg.g-1 of total LAB) samples. Similar profiles of LAB congeners were found for the detergents and LAS samples indicating that identical surfactants. In some samples, LAB were not found (limit of detection < 0.2 mg.mL-1).

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.

O alquil benzeno sulfonato linear (LAS) é o principal tensoativo aniônico, largamente utilizado em detergentes. O alquil benzeno linear (LAB), um subproduto, faz uma associação ao tensoativo devido a sulfonação incompleto do LAS. Recentemente tem tido grande interesse de usá-lo como marcador de efluente doméstico no ambiente aquático. Neste estudo, um novo método para determinação de LAB em detergentes envolvendo cromatografia a gás acoplado a espectrometria de massa em combinação com microextração em fase sólida (SPME) é proposto. O planejamento fatorial foi utilizado para obter valores ótimos para os principais parâmetros de análises de LAB em detergentes usando SPME direto como etapa de pré-concentração. SPME-GC/MS combinada com análise de componentes principais (PCA) e empregada para avaliar os parâmetros que afetam a SPME. O método otimizado foi aplicado nas amostras de detergentes comerciais (0,97 a 3,67 mg.g-1 LAB totais) e LAS (24,7 mg.g-1 LAB totais). Um perfil similar foi encontrado entre as amostras de detergentes e o LAS indicando que os tensoativos são idênticos. E algumas amostras, os LAB não foram encontrados (limite de detecção < 0,2 µg.mL-1). / Linear Alkylbenzene Sulfonated (LAS) is the main anionic surfactant, wide used in detergents. The Linear Alkylbenzene (LAB), a by-product, makes association with the surfactant, due the incomplete sulfonation of the LAS. Recently there has been widespread interest in their use as markers tracers of domestic waste in the aquatic environment. In this study, a new method for determination of LAB in detergents involving gas chromatography coupled to mass spectrometry (GC-MS) in combination with Solid Phase Microextraction (SPME) is proposed. A factorial design was utilized to obtain the optimum values for the main operation parameters in the analysis of LAB in detergents using direct SPME in the pre-concentration step. SPME-GC/MS in combination whit principal component analysis (PCA) was employed to evaluate the parameters that affect on SPME. The optimized method was applied to commercial detergents (0.97 and 3.67 mg.g-1 of total LAB) and LAS ( 24.47 mg.g-1 of total LAB) samples. Similar profiles of LAB congeners were found for the detergents and LAS samples indicating that identical surfactants. In some samples, LAB were not found (limit of detection < 0.2 mg.mL-1).

The long-term complications of diabetes can be dramatically reduced with tight glycemic control. Although the current invasive technology for measuring blood glucose is effective, it not well suited for the real-time measurements necessary for tight control. Near infrared (NIR) absorption spectroscopy, coupling with multivariate calibration modeling, can potentially provide portable, rugged and low-cost instrumentation for continuous glucose sensing. An optical microsensor that can be used in conjunction with an ultrafiltration sampling probe is under development for continuous glucose measurements in interstitial fluid (ISF) collected from subcutaneous tissue. The first part of this research focused on the development of an algorithm for eliminating of effect of temperature variance on NIR glucose measurements. Spectra of 80 bovine blood ultrafiltrate samples were collected under five different temperatures by using a Fourier transform (FT) NIR spectrometer. Based on the fundamental properties of digital Fourier filtering, baseline variations created by difference in the temperature of the blood ultrafiltrate samples were shown to be eliminated by using an optimized Gaussian shape filter response function. PLS calibration models combined with digital Fourier filtering provided standard errors of prediction in the range of 0.3-0.4 mM for sample with temperatures between 25-40 °C. Before applying the microsensor to animal or human measurements, a testing platform was designed and constructed for the eventual purpose of evaluating the ability of the microsensor to follow glucose concentration transients. A series of computer-controlled pumps were used in combination with an ultrafiltration probe to create glucose transients and deliver the corresponding samples to the spectrometer for analysis. NIR spectra were collected continuously as the concentrations of glucose, urea, and lactate were varied independently. Glucose transients were followed over periods of days by using either partial least squares (PLS) or net analyte signal (NAS) calibration methods. The NAS calibration method and a modified Hybrid Linear Analysis (HLA) method were investigated for monitoring the concentrations of glucose and lactate during microbial fermentations. An UF-sampling probe is used to collect samples of the fermentation broth and deliver these samples to the spectrometer for continuous analysis. The established NAS and modified-HLA calibration models provided glucose and lactate concentration measurements with mean percentage errors of 2 and 3%, respectively. These calibration functions were demonstrated capable of accurate concentration measurements several days beyond the formal calibration process. Lastly, NIR spectra of whole bovine blood samples were used to demonstrate the ability to measure glucose in blood with different levels of hematocrit. Calibration functions were based on PLS modeling and the effective models were developed for measurements from absorbance and single-beam NIR spectra. The method of multiplicative scatter correction was found to be particularly effective in reducing the impact of light scattering caused by the red blood cells at different hematocrit levels. These findings imply that nondestructive NIR spectroscopy has the potential to measure glucose without consuming blood, thereby reducing phlebotomy blood loss in neonates and potentially decreasing the frequency of red blood cell transfusion for this fragile patient population.

Noninvasive glucose monitoring has been the subject of considerable research because of the high number of diabetes patients who must monitor their glucose levels daily by taking blood samples. Among methods being evaluated for possible use in this application, near-infrared (NIR) spectroscopy has received significant attention because of available glucose absorption bands that can be observed in the presence of the large aqueous background found in tissue spectra. The objective of the research presented here is to evaluate the potential for implementing a noninvasive nocturnal hypoglycemic alarm with NIR spectroscopy. Such an alarm would be used by a diabetic to detect potentially dangerous occurrences of hypoglycemia during sleep. The approach used is to collect spectra continuously from the patient during the sleep period, followed by the application of pattern recognition methods to determine if a spectrum represents a blood glucose level that exceeds a hypoglycemic threshold. A reference spectrum is collected and a conventional finger-stick glucose concentration measurement is made at the start of the sleep period. The ratio is then taken of each subsequent spectrum to the collected reference, forming a differential spectrum corresponding to the signed difference in concentration relative to the reference. The identification of these differential spectra as "alarm" or "non-alarm" is performed with a classification model computed with piecewise linear discriminant analysis. This methodology is initially tested with in vitro laboratory data that simulated the glucose excursions that occur during sleep. The performance of the hypoglycemic alarm methodology in the presence of varying levels of urea, glyceryl triacetate, and L-lactate as potential spectral interferents is tested. The robustness of the methodology with respect to time is also evaluated. The thesis further discusses an experimental procedure to prepare tissue phantoms composed of two main proteins that exist in human skin tissue, keratin and collagen. A new methodology is developed to produce varying-thickness films that allowed the simulation of changes in the content of skin tissue proteins present within the optical path of the NIR measurement. The prepared films are incorporated into in vitro laboratory measurements in which varying levels of glucose, urea, keratin, and collagen are introduced in order to provide a test of the hypoglycemic alarm algorithm that simulates the spectral properties of human tissue. Finally, the hypoglycemic alarm algorithm is tested with in vivo data collected with rat animal models. Data are presented for single-day experiments performed with anesthetized rats, as well as for multiple-day experiments conducted with awake rats. The results obtained from both the in vitro and in vivo studies confirm that if high-quality spectral data are attainable, the alarm methodology can work effectively to identify hypoglycemic events while exhibiting a low rate of false detections.

Thesis (Master of Applied Sciences in Chemistry)--Cape Peninsula University of Technology, 2018. / The high demand of omega-3 fish oil nutraceuticals (dietary supplements) is due to the numerous health benefits contributed by the polyunsaturated fatty acids (PUFA’s). The nutraceutical industry is required to follow good manufacturing practice (GMP) standards in order to ensure label claims and prevent adulteration. It is vital that the quality control (QC) procedures will be able to detect adulterated products. It is thus necessary to ensure the analytical techniques are adequate by using validated methods. The qualification or identification of natural fish oils is a difficult task due to overlapping concentration ranges of PUFA’s and other similar properties. Gas chromatography (GC) is the prescribed technique in the nutraceutical industry for analysis of omega-3 fatty acids, but it is time-consuming and costly. Near infrared (NIR) spectroscopy is a rapid and cost-effective technique that can replace the prescribed method if proven equivalent, through validation according to pharmaceutical criteria. In this study, NIR spectroscopy in combination with chemometrics was considered as an alternative method to GC, to identify various commercial fish oils and to quantify the PUFA’s. Identification methods were developed for nine commercial omega-3 fish oils using spectral libraries. Quantitative NIR methods were developed for arachidonic acid (AA), docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) in fish oils expressed as mg.g-1 as well as percentage (%) area using partial least squares (PLS) regression and independent validation by superimposing datasets with mutual properties. Based on the statistics in terms of SEC, R2, SEP and r of the PUFA models, the NIR method was equivalent to the prescribed GC methods and precision results obtained were within the prescribed criteria. NIR spectroscopy and chemometrics can be used for conclusive identification and quantification of omega-3 fish oils, thereby minimizing the risk of adulteration. The method also complied with the prescribed pharmaceutical method validation criteria; therefore, was demonstrated as an alternative method to GC for the nutraceutical industry.

The U.S Environmental Protection Agency (USEPA) Airborne Spectral Photometric Environmental Collection Technology (ASPECT) program is designed in part to provide first responders with radiological mapping of potentially hazardous locations. This program utilizes an aircraft fitted with a gamma-ray spectrometer capable of remote detection of radioisotopes. The challenges present in detecting a radioisotope signal remotely are strongly tied to the signal-to-noise ratio of the collected gamma-ray spectra and the specific signal processing and pattern recognition methods used in the data analysis. Depending on the distance from the detector to the radioisotope source, Compton scattering can significantly reduce the analyte signal, and weakened signals pose a significant challenge when attempting to design an effective classifier for detecting radioisotopes of interest. In this research, a basic methodology has been developed for the detection of cesium-137 (¹³⁷Cs) and cobalt-60(⁶⁰Co) utilizing only laboratory collected spectra and backgrounds from the field collected only once. The presented classifier methodology has been proven to provide a fundamental structure for which more advanced algorithms can be developed. Furthermore, this methodology has demonstrated the ability to strongly associate a level of confidence in a detection which allows for intelligent decision making. From this basic methodology, more sensitive and selective algorithms can be designed. The Compton effect has previously been problematic in the development of gamma-ray pattern recognition systems. In this research, a background suppression methodology utilizing linear regression has been implemented to enhance the basic pattern recognition methodology. This background correction strategy has led to significant improvements in the remote detection of radioisotopes and enables the classification of more complex radioisotopes such as europium-152 (¹⁵²Eu). This research demonstrates not only the capabilities of the pattern recognition methodology, but also the flexibility of the procedure. In the remote detection of radioisotopes, false detections and low sensitivity are the key challenges when developing a classifier. While the background corrected methodology was shown to greatly enhance the classifier performance, further advances can be made into the methodology through the use of committee classifiers. Since every classifier utilizes a different dataspace, a standardization procedure has been developed from which the classifier result can be averaged and generate a committee classifier result. This classifier methodology has been demonstrated to further improve the radioisotope classifier performance without sacrificing either sensitivity or selectivity. While the development of targeted radioisotope classifiers is invaluable to the first responder, developing a general gamma-ray anomaly classifier can handle those radioisotopes that have no dedicated classifier. From this objective, a unique anomaly classifier based on the Compton region of the gamma-ray spectrum has been developed and demonstrated to operate in the field. Utilizing all of the strategies and techniques developed for single radioisotope classifiers, the anomaly classifier has been proven to detect background and natural radioactive sources as well as controlled and man-made radioisotope targets. From the developed remote detection classifiers via pattern recognition techniques, robust radiation detection classifiers have been developed. This pattern recognition methodology eschews the need for extensive field data collection for training the algorithms, while also removing the need for on-site calibrations. When used in conjunction with one another, the dedicated radioisotope and anomaly classifiers provide a thorough and rugged remote detection capability to the first responder. The presented methodology also demonstrates that any radioisotope classifier can be generated, implying that this method can be used for the detection of any radioisotope in the field.

<p>This thesis presents a novel bioinformatic methodology denoted the bio-chemometric approach. The methodology is designed for generation of detailed descriptions and predictions of biomolecular interactions. It is based on multivariate analysis of the sensitivity of a biomolecular interaction to multiple minor changes in the experimental conditions. In this work, either the chemical environment where the interaction takes place, or the molecular structure of one of the interacting molecules, was varied. The sensitivity of the interaction to the performed variations was presented as a vector called the sensitivity fingerprint. The bio-chemometric approach was tested on several biomolecular interactions. Useful descriptions of the interactions were obtained by measuring binding kinetics for each interaction in 12-20 different buffers and correlating buffer composition to binding kinetics. The obtained chemical sensitivity fingerprints were reproducible, significantly different and showed a weak correlation to binding site properties for the tested interactions. The results indicate that the fingerprints contained useful information about the binding site. The predictive ability of the bio-chemometric approach was tested on two different biomolecular interactions where one of the binding partners was slightly modified into multiple analogues by amino acid exchanges. In one example, interactions of 18 peptide analogues with an antibody gave data that could be used for accurate prediction of the dissociation rates of novel analogues. Reliable predictions of binding kinetics and affinity were also obtained for single domain camel antibody analogues binding to a protein antigen. By using the three-dimensional structure of camel antibodies and data obtained using the bio-chemometric approach, even the importance of non-exchanged amino acids for the binding could be estimated. The bio-chemometric approach can potentially improve the development of peptides and proteins for therapeutic and diagnostic use. It is suggested to be valid for general use in biochemistry.</p>

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.