Associação do polimorfismo r72p do gene tp53 com o prognóstico do câncer de mama

O câncer de mama é o segundo tipo decâncer mais freqüente no mundo e o mais comumentre as mulheres. Cerca de 22% novos casos decâncer de mama em mulheres são reportados porano, constituíndo um grave problema de saúdepública. Polimorfismos genéticos são variaçõesem seqüências nucleotídicas que podem alterarquantitativamente o fenotípo. A proteína p53monitora a integridade do genoma controlandopontos de checagem durante o ciclo celular e é osupressor tumoral mais comumente alterado nocâncer humano. O polimorfismo no códon 72(R72P) envolve códons para prolina (CCC,TP53Pro) ou arginina (CGC, TP53Arg), ambosassociados ao risco de carcinogênese. Apesar davariante com arginina induzir mais eficientementea apoptose em células cancerosas, ele apresentamaior susceptibilidade ao câncer de mama que avariante com prolina. Os resultados permanecemcontraditórios, pois os valores de risco do R72Pvariam de acordo com o perfil étnico e geográficodo paciente. O presente estudo é uma revisãosobre a associação do R72P com o câncer demama em mulheres de diferentes etnias e sítiosgeográficos. Esses resultados podem fornecerparâmetros com potencial valor clínico

In situ short-term responses of Amazonian understory plants to elevated CO₂

The response of plants to increasing atmospheric CO2 depends on the ecological context where the plants are found. Several experiments with elevated CO2 (eCO2) have been done worldwide, but the Amazonian forest understory has been neglected. As the central Amazon is limited by light and phosphorus, understanding how understory responds to eCO2 is important for foreseeing how the forest will function in the future. In the understory of a natural forest in the Central Amazon, we installed four open-top chambers as control replicates and another four under eCO2 (+250 ppm above ambient levels). Under eCO2, we observed increases in carbon assimilation rate (67%), maximum electron transport rate (19%), quantum yield (56%), and water use efficiency (78%). We also detected an increase in leaf area (51%) and stem diameter increment (65%). Central Amazon understory responded positively to eCO2 by increasing their ability to capture and use light and the extra primary productivity was allocated to supporting more leaf and conducting tissues. The increment in leaf area while maintaining transpiration rates suggests that the understory will increase its contribution to evapotranspiration. Therefore, this forest might be less resistant in the future to extreme drought, as no reduction in transpiration rates were detected.</p

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

AVALIAÇÃO DE SOBREVIDA E EXPRESSÃO DA PROTEÍNA c-erbB-2, RECEPTORES DE PROGESTERONA E RECEPTORES DE ESTRÓGENO EM PACIENTES COM CÂNCER DE MAMA

Made available in DSpace on 2016-08-10T10:38:33Z (GMT). No. of bitstreams: 1 FLAVIA ALEIXO FERREIRA.pdf: 856261 bytes, checksum: 437e20f50936aac2d69cf7dcc15d95ed (MD5) Previous issue date: 2011-07-01Breast cancer is the second most frequent type of cancer worldwide and more common among women, accounting for 22% of new cases each year. These tumors appear as heterogeneous evolution and response to different treatment available whose prognostic and predictive factors guiding the therapeutic approach being used. The detection of oncogenic protein c-erbB-2 by immunohistochemistry is a prognostic factor for diagnostic, and in most cases, is associated with a worse prognosis. This study aimed to raise clinicopathological data of patients with breast cancer, as well as evaluating the expression c-erbB-2 in tumor tissue paraffin samples of these patients. Medical records of 286 female patients with breast carcinoma treated at Hospital Araújo Jorge (Association of Cancer Combat of Goiás), between 1979 and 2002 were collected and tabulated together with data from immunohistochemical detection of c-erbB protein -2. In our series the positive immunodetection of c-erbB-2 in tumor cells showed no association with conventional parameters clinicopathologics. The immunodetection of the protein c-erbB-2 did not significantly affect the survival of patients analyzed in our series, consistent with data obtained by other studies. We conclude that molecular methods should become more sensitive.O câncer de mama é o segundo tipo mais frequente de câncer no mundo e o mais comum entre as mulheres, corresponde por 22% dos casos novos a cada ano. Esses tumores apresentam-se heterogêneos quanto a evolução e resposta às diferentes opções terapêuticas disponíveis, cujos fatores prognósticos e preditivos norteiam a conduta terapêutica a ser utilizada. A detecção da proteína oncogênica c-erbB-2 por imuno- histoquímica é um fator prognóstico auxiliar para avaliação diagnóstica e, na maioria dos casos, associa-se a um pior prognóstico. O presente estudo teve como objetivo levantar os dados clínicopatológicos de pacientes com câncer de mama, bem como avaliar a expresssão de c-erbB-2 nas amostras de tecido tumoral parafinadas dessas pacientes. Prontuários de 286 pacientes do sexo feminino com carcinoma de mama atendidas no Hospital Araújo Jorge (Associação de Combate ao Câncer em Goiás), entre 1979 e 2002, foram coletados e tabulados juntamente com os dados de imuno- histoquímica para detecção da proteína c-erbB-2. Em nossa casuística a imunodetecção positiva de c-erbB-2 nas células tumorais não demonstrou associação com os parâmetros clinicopatológicos convencionais. A imunodetecção da proteína c-erbB-2 não influenciou significativamente a sobrevida das pacientes analisadas em nossa série, condizendo com dados obtidos por outros estudos. Assim concluímos que os métodos moleculares devem se tornar mais sensívei

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq