XIAP and P-glycoprotein co-expression is related to imatinib resistance in chronic myeloid leukemia cells

AbstractP-glycoprotein (Pgp) and XIAP co-expression has been discussed in the process of the acquisition of multidrug resistance (MDR) in cancer. Here, we evaluated XIAP and Pgp expression in chronic myeloid leukemia (CML) samples, showing a positive correlation between them. Furthermore, we evaluated the effects of imatinib in XIAP and Pgp expression using CML cell lines K562 (Pgp−) and K562-Lucena (Pgp+). Imatinib increased XIAP and Pgp expression in K562-Lucena cells, while in K562 cells a downregulation of these proteins was observed, suggesting that imatinib induces an increment of MDR phenotype of CML cells that previously exhibit high levels of Pgp/XIAP co-expression

Detecção da proteína p53 em células leucêmicas por citometria de fluxo e Western blot

Introdução: A proteína p53 desempenha uma função crucial no controle do ciclo celular, reparo do DNA e na indução de apoptose em células geneticamente instáveis. O Western blot (WB) é o método preconizado para detecção dessa proteína, no entanto é técnica demorada e trabalhosa. Atualmente, a citometria de fluxo (CF) também tem sido empregada na detecção da proteína p53 tendo a vantagem da praticidade. Objetivos e Metodologia: Comparar os resultados obtidos pela CF e WB na detecção da proteína p53 em células leucêmicas. Empregamos amostras de 3 pacientes com leucemia linfóide aguda (LLA), 5 com leucemia mielóide aguda (LMA), 6 com leucemia mielóide crônica (LMC) e 8 com leucemia linfóide crônica (LLC). Os controles positivos (5) e negativos (4), para os dois métodos, foram linhagens de células leucêmicas. Juntamente com o controle de marcação negativa, na técnica de CF, utilizamos linfócitos de 40 doadores de sangue. A análise pela CF foi realizada após a marcação com anticorpo monoclonal anti-p53 e o WB por técnica convencional. Resultados e Conclusões: Observamos concordância nos resultados em 82% das amostras leucêmicas e em 100% nas linhagens celulares. CF+/WB+ foram observados em pacientes com evolução desfavorável tais como na LLC / Síndrome de Richter, LMC em crise blástica e na maioria das LMA. Apesar do WB ser considerado um método padrão para a detecção da p53, nossos resultados indicam que a CF pode ser empregada satisfatoriamente na detecção dessa proteína em amostras leucêmicas

AS REPRESENTAÇÕES SOCIAIS DO CÂNCER DE MAMA E NO COLO DO ÚTERO NO CONHECIMENTO DA ENFERMAGEM BRASILEIRA

Trata-se de uma pesquisa documental cujo objetivo caracterizar as representações sociais sobre o câncer ginecológico presentes nas teses e dissertações da enfermagem brasileira no período de 2001 a 2007. A fonte de pesquisa foi o Banco de Teses e Dissertações da Associação Brasileira de Enfermagem. Foram identificados 51 estudos. A análise dos dados originou as seguintes categorias temáticas: Os aspectos psicossociais de pacientes com câncer; As representações sociais do câncer feminino; O cotidiano da mulher com câncer de mama e no colo do útero; Prevenção e tratamento: o papel do enfermeiro. Os estudos propiciaram apreender os aspectos do contexto psicossocial, tão importantes e necessários no sentido de olhar mais atentamente a prática assistencial da enfermagem

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

Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 – 2018

São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

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

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