928 resultados para National Cancer Institute (U.S.). Viral Oncology Program
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This thesis is focused on the design and synthesis of a diverse range of novel organosulfur compounds (sulfides, sulfoxides and sulfones), with the objective of studying their solid state properties and thereby developing an understanding of how the molecular structure of the compounds impacts upon their solid state crystalline structure. In particular, robust intermolecular interactions which determine the overall structure were investigated. These synthons were then exploited in the development of a molecular switch. Chapter One provides a brief overview of crystal engineering, the key hydrogen bonding interactions utilized in this work and also a general insight into “molecular machines” reported in the literature of relevance to this work. Chapter Two outlines the design and synthetic strategies for the development of two scaffolds suitable for incorporation of terminal alkynes, organosulfur and ether functionalities, in order to investigate the robustness and predictability of the S=O•••H-C≡C- and S=O•••H-C(α) supramolecular synthons. Crystal structures and a detailed analysis of the hydrogen bond interactions observed in these compounds are included in this chapter. Also the biological activities of four novel tertiary amines are discussed. Chapter Three focuses on the design and synthesis of diphenylacetylene compounds bearing amide and sulfur functionalities, and the exploitation of the N-H•••O=S interactions to develop a “molecular switch”. The crystal structures, hydrogen bonding patterns observed, NMR variable temperature studies and computer modelling studies are discussed in detail. Chapter Four provides the overall conclusions from chapter two and chapter three and also gives an indication of how the results of this work may be developed in the future. Chapter Five contains the full experimental details and spectral characterisation of all novel compounds synthesised in this project, while details of the NCI (National Cancer Institute) biological test results are included in the appendix.
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Todos os anos, milhares de pessoas morrem vítimas de doenças causadas pelo consumo de produtos derivados do tabaco, este é considerado a principal causa de morte evitável. O tabaco também colabora com as seis das oito principais causas de mortes entre fumantes e não fumantes a nível mundial. Algumas medidas governamentais como as campanhas publicitárias antitabagistas, buscam alertar, conscientizar e mudar o pensamento e o interesse coletivo neste tipo de produto e consequentemente, diminuir a taxa de consumo. Avaliar se as crenças, pensamentos e atitudes dos brasileiros são influenciados por este tipo de publicidade e se o comportamento relacionado a não fumar ou deixar de fumar é uma consequência da persuasão das mensagens antitabagistas, ajudam a conhecer o real impacto destas campanhas e sua eficácia. Através dos métodos de investigação quantitativo e qualitativo e das análises extensiva e semiótica, a pesquisa inquiriu 272 indivíduos brasileiros à respeito das advertências sanitárias e das campanhas publicitárias antitabagistas, classificando-os como não fumantes, ex-fumantes e fumantes, identificando os elementos visuais e textuais que compõem a narrativa publicitária de 5 anúncios antitabagistas. Após a análise, a pesquisa concluiu que as campanhas publicitárias coordenadas pelo INCA – Instituto Nacional de Câncer, denominadas campanhas antitabagistas, são eficazes para alertar e conscientizar os indivíduos sobre os males causados pelo consumo do cigarro mas ineficazes para influenciar suas atitudes e comportamentos. Embora estas consigam persuadir à crença nas mensagens, fazendo com que os indivíduos as vejam como verdadeira, isto não é suficiente para que a intenção de deixar de fumar torne-se um ato prático. Todos os anúncios possuem o mesmo formato e a maioria utilizou o mesmo percurso visual, equilíbrio, enquadramento, luz, ângulo e função do personagem. Todos possuem textos com funções identificadora, ancoragem e apoio e a narrativa conota o cigarro como algo negativo, prejudicial, mortífero e destruidor.
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En esta investigación se realiza un análisis del tipo de relaciones que se establecen entre la medicina alopática y la medicina indígena yagecera en el escenario urbano de Bogotá. Para ello, toma distancia de los estudios ya realizados sobre este tema en el campo de la antropología a partir de dos aspectos: en primer lugar, busca acercarse a esta relación a partir de las trayectorias profesionales de un conjunto de médicos (tanto indígenas como alopáticos); en segundo lugar, se aproxima a estas relaciones a partir de una enfermedad particular: el cáncer.
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El diagnóstico de cáncer de tiroides se ha incrementado y las posibilidades de detección de una enfermedad subclínica son altas, toda vez que disponemos de herramientas de detección más sensibles y de fácil acceso. Por ende, el clínico requiere conocer la historia natural del nódulo tiroideo y del carcinoma papilar de tiroides de bajo riesgo para brindar a su paciente el mejor tratamiento basado en la evidencia clínica. El objetivo de esta revision es reconocer los elementos clínicos que han condicionado el aumento inusitado de casos de cáncer de tiroides. Conclusión: El sobrediagnóstico del cáncer de tiroides es una realidad, que se posibilita por el uso extendido de biopsia por aspiración con aguja fina ((BACAF)) después de la detección de un nódulo tiroideo, en gran parte de manera incidental, sin acarrear la mayoría de las veces un mejor pronóstico después de su tratamiento.
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Se conformó el primer archivo docente digital de patología específica del seno en la modalidad de mamografía a nivel nacional, el cuál permitirá el entrenamiento de radiólogos y residentes de radiología según el sistema de lectura BI-RADS, buscando la unificación de criterios y mejoría de las competencias en la interpretación de las imágenes con la finalidad de aumentar la detección temprana del carcinoma de seno
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Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.
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With many cancers showing resistance to current chemotherapies, the search for novel anti-cancer agents is attracting considerable attention. Natural flavonoids have been identified as useful leads in such programmes. However, since an in-depth understanding of the structural requirements for optimum activity is generally lacking, further research is required before the full potential of flavonoids as anti-proliferative agents can be realised. Herein a broad library of 76 methoxy and hydroxy flavones, and their 4-thio analogues, was constructed and their structure-activity relationships for anti-proliferative activity against the breast cancer cell lines MCF-7 (ER+ve), MCF-7/DX (ER+ve, anthracycline resistant) and MDA-MB-231 (ER-ve) were probed. Within this library, 42 compounds were novel, and all compounds were afforded in good yields and > 95% purity. The most promising lead compounds, specifically the novel hydroxy 4-thioflavones 15f and 16f, were further evaluated for their anti-proliferative activities against a broader range of cancer cell lines by the National Cancer Institute (NCI), USA and displayed significant growth inhibition profiles (e.g Compound-15f: MCF-7 (GI50 = 0.18 μM), T-47D (GI50 = 0.03 μM) and MDA-MB-468 (GI50 = 0.47 μM) and compound-16f: MCF-7 (GI50 = 1.46 μM), T-47D (GI50 = 1.27 μM) and MDA-MB-231 (GI50 = 1.81 μM). Overall, 15f and 16f exhibited 7-46 fold greater anti-proliferative potency than the natural flavone chrysin (2d). A systematic structure-activity relationship study against the breast cancer cell lines highlighted that free hydroxyl groups and the B-ring phenyl groups were essential for enhanced anti-proliferative activities. Substitution of the 4-C=O functionality with a 4-C=S functionality, and incorporation of electron withdrawing groups at C4’ of the B-ring phenyl, also enhanced activity. Molecular docking and mechanistic studies suggest that the anti-proliferative effects of flavones 15f and 16f are mediated via ER-independent cleavage of PARP and downregulation of GSK-3β for MCF-7 and MCF-7/DX cell lines. For the MDA-MB-231 cell line, restoration of the wild-type p53 DNA binding activity of mutant p53 tumour suppressor gene was indicated.
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Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.
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We consider consider the problem of dichotomizing a continuous covariate when performing a regression analysis based on a generalized estimation approach. The problem involves estimation of the cutpoint for the covariate and testing the hypothesis that the binary covariate constructed from the continuous covariate has a significant impact on the outcome. Due to the multiple testing used to find the optimal cutpoint, we need to make an adjustment to the usual significance test to preserve the type-I error rates. We illustrate the techniques on one data set of patients given unrelated hematopoietic stem cell transplantation. Here the question is whether the CD34 cell dose given to patient affects the outcome of the transplant and what is the smallest cell dose which is needed for good outcomes. (C) 2010 Elsevier BM. All rights reserved.
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Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Maxine Frank Singer began her education in the New York City public schools and earned her baccalaureate degree from Swarthmore College and her Ph.D. in biochemistry from Yale University. Dr. Singer has had a long association with the National Institutes of Health and served as Chief, Laboratory of Biochemistry, National Cancer Institute, where she now carries the title of Scientist Emerita. In 1988, she became President of the Carnegie Institution of Washington and served in that capacity until 2002 when she was named President Emerita and Senior Scientific Advisor to the Carnegie Academy for Science Education.