Viscum album mother tinctures: Harvest conditions and host trees influence the plant metabolome and the glycolytic pathway of breast cancer cells.

Viscum album is a semi-parasitic plant used for over one hundred years in complementary cancer therapy. The main commercial drugs used in cancer patients' treatment are derived from the aqueous V. album extracts, whose cytotoxic potential is mostly attributed to the aqueous soluble antitumoral metabolites. On the counterpart, ethanol solvents must be used to obtain V. album mother tinctures. This methodology permits better solubilization of phenolic compounds, among others, which present antitumoral bioactivity. Recently, the metabolomics approach revealed the influence of the host tree on the V. album subspecies differentiation. To increase the scientific information about the chemical differences related to the host trees and to clarify the seasonal influences, in this study, the metabolome of 50 V. album mother tinctures from three subspecies (abietis, album, austriacum) and five host trees (Malus domestica, Quercus sp., Ulmus carpinifolia, Pinus sylvestris, Abies alba) was evaluated using summer and winter plant harvests. The in vitro cytotoxic activities were investigated in breast cancer cells (MDA-MB-231) and immortalized normal human keratinocytes (HaCaT). The summer V. album mother tinctures presented higher cytotoxic activity than winter ones. Among the summer samples, those prepared with V. album subsp. album were more cytotoxic than V. album subsp. abietis and subsp. V. album subsp. austriacum. The V. album harvested from Quercus petraea and Abies alba inhibited the key-glycolytic enzymes: hexokinase (HK), phosphofructokinase (PFK), pyruvate kinase (PK). This activity was related to a reduction in glucose uptake and lactate production, which were host-tree-time-dose-dependent. The untargeted metabolomic approach was able to discriminate the mother tinctures according to respective botanical classes and harvest season. A total of 188 metabolites were annotated under positive and negative modes. Fourteen compounds were responsible for the samples differentiation, and, to the best of our knowledge, eight were described in the Viscum album species for the first time. Our study shows the interruption of the Warburg effect as a novel antitumoral mechanism triggered by V. album mother tinctures, which is related to their metabolite profile. These results bring scientific evidence that encourages the use of V. album mother tinctures as a natural product for cancer therapy

UM ESTUDO DE MAPEAMENTO SISTEMÁTICO DA MINERAÇÃO DE DADOS PARA CENÁRIOS DE BIG DATA

O volume de dados produzidos tem crescido em larga escala nos últimos anos. Esses dados são de diferentes fontes e diversificados formatos, caracterizando as principais dimensões do Big Data: grande volume, alta velocidade de crescimento e grande variedade de dados. O maior desafio é como gerar informação de qualidade para inferir insights significativos de tais dados variados e grandes. A Mineração de Dados é o processo de identificar, em dados, padrões válidos, novos e potencialmente úteis. No entanto, a infraestrutura de tecnologia da informação tradicional não é capaz de atender as demandas deste novo cenário. O termo atualmente conhecido como Big Data Mining refere-se à extração de informação a partir de grandes bases de dados. Uma questão a ser respondida é como a comunidade científica está abordando o processo de Big Data Mining? Seria válido identificar quais tarefas, métodos e algoritmos vêm sendo aplicados para extrair conhecimento neste contexto. Este artigo tem como objetivo identificar na literatura os trabalhos de pesquisa já realizados no contexto do Big Data Mining. Buscou-se identificar as áreas mais abordadas, os tipos de problemas tratados, as tarefas aplicadas na extração de conhecimento, os métodos aplicados para a realização das tarefas, os algoritmos para a implementação dos métodos, os tipos de dados que vêm sendo minerados, fonte e estrutura dos mesmos. Um estudo de mapeamento sistemático foi conduzido, foram examinados 78 estudos primários. Os resultados obtidos apresentam uma compreensão panorâmica da área investigada, revelando as principais tarefas, métodos e algoritmos aplicados no Big Data Mining

Clotrimazole Preferentially Inhibits Human Breast Cancer Cell Proliferation, Viability and Glycolysis

BACKGROUND: Clotrimazole is an azole derivative with promising anti-cancer effects. This drug interferes with the activity of glycolytic enzymes altering their cellular distribution and inhibiting their activities. The aim of the present study was to analyze the effects of clotrimazole on the growth pattern of breast cancer cells correlating with their metabolic profiles. METHODOLOGY/PRINCIPAL FINDINGS: Three cell lines derived from human breast tissue (MCF10A, MCF-7 and MDA-MB-231) that present increasingly aggressive profiles were used. Clotrimazole induces a dose-dependent decrease in glucose uptake in all three cell lines, with K(i) values of 114.3±11.7, 77.1±7.8 and 37.8±4.2 µM for MCF10A, MCF-7 and MDA-MB-231, respectively. Furthermore, the drug also decreases intracellular ATP content and inhibits the major glycolytic enzymes, hexokinase, phosphofructokinase-1 and pyruvate kinase, especially in the highly metastatic cell line, MDA-MB-231. In this last cell lineage, clotrimazole attenuates the robust migratory response, an effect that is progressively attenuated in MCF-7 and MCF10A, respectively. Moreover, clotrimazole reduces the viability of breast cancer cells, which is more pronounced on MDA-MB-231. CONCLUSIONS/SIGNIFICANCE: Clotrimazole presents deleterious effects on two human breast cancer cell lines metabolism, growth and migration, where the most aggressive cell line is more affected by the drug. Moreover, clotrimazole presents little or no effect on a non-tumor human breast cell line. These results suggest, at least for these three cell lines studied, that the more aggressive the cell is the more effective clotrimazole is

Latin America: Reduced S&T Investment Puts Sustainable Development at Risk

Latin America is home to more than 600 million people and has considerable natural and human resources. However, investment in science and technology (S&T) lags far behind that in developed countries. This gap represents a barrier to the development of economies based on knowledge and hampers the region's ability to tackle environmental and social problems. This lack of investment is evident in the extreme case of Venezuela, where much of the science workforce has fled economic chaos, but also in every Latin American country, including science powers such as Brazil and Argentina, where federal budgets in science, technology and education have been drastically reduced in recent years. Investments in S&T foster cooperation, commerce and good will and enhance resilience in the face of environmental and social turmoil. Therefore, scientists must start to actively engage governments and encourage long-term spending in S&T to support the development of Latin American societies.Universidad de Costa Rica/[]/UCR/Costa RicaSistema Nacional de Investigación/[]/SNI/SENACYT/PanamáUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Estación Experimental Agrícola Fabio Baudrit Moreno (EEAFBM)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Jardín Botánico Lankester (JBL

Análise da construção de modelos preditivos sob a perspectiva de indicadores de evasão

A predição de evasão de alunos com base em modelos que utilizam dados oriundos de ambientes virtuais de aprendizagem é um tema de pesquisa que desperta interesse por auxiliar na gestão acadêmica. Foi constatado em um estudo anterior que três indicadores principais sinalizam a evasão: comportamento do aluno, desempenho do aluno e aspectos demográficos. Apesar de que os modelos de predição de evasão encontrados na literaturafazem uso de alguns dados que caracterizam esses indicadores, não está claro o quanto os indicadores orientam a construção dos modelos preditivos. Uma análise de modelos preditivos reportados em estudos primários foi realizada para identificar como os indicadores de desempenho, comportamental e demográfico são utilizados na construção dos modelos de predição de evasão. Os resultados obtidos revelam que a maioria dos modelos preditivos, independente do indicador de evasão, faz uso da mineração de dados. Adicionalmente, os indicadores de evasão abordados pelos modelos preditivos, implementam em sua maioria métodos de árvore de decisão. Por fim, a métrica mais usada para avaliar os modelos preditivos é a precisão/acurácia, também independente dos indicadores de evasão

Effects of Food Additives on Immune Cells As Contributors to Body Weight Gain and Immune-Mediated Metabolic Dysregulation

Food additives are compounds used in order to improve food palatability, texture, and shelf life. Despite a significant effort to assure safety of use, toxicological analysis of these substances, generally, rely on their direct toxicity to target organs (liver and kidney) or their genotoxic effects. Much less attention is paid to the effects of these compounds on cells of the immune system. This is of relevance given that metabolic dysregulation and obesity have a strong immune-mediated component. Obese individuals present a state of chronic low-grade inflammation that contributes to the establishment of insulin resistance and other metabolic abnormalities known as the metabolic syndrome. Obesity and metabolic syndrome are currently recognized as worldwide epidemics that pose a profound socioeconomic impact and represent a concern to public health. Cells of the immune system contribute to both the maintenance of “lean homeostasis” and the metabolic dysregulation observed in obese individuals. Although much attention has been drawn in the past decades to obesity and metabolic syndrome as a result of ingesting highly processed food containing large amounts of fat and simple sugars, mounting evidence suggest that food additives may also be important contributors to metabolic derangement. Herein, we review pieces of evidence from the literature showing that food additives have relevant effects on cells of the immune system that could contribute to immune-mediated metabolic dysregulation. Considering their potential to predispose individuals to develop obesity and metabolic syndrome, their use should be taken with caution or maybe revisited

Nanomicellar Formulation of Clotrimazole Improves Its Antitumor Action toward Human Breast Cancer Cells.

Although demonstrated as a selective anticancer drug, the clinical use of clotrimazole (CTZ) is limited due to its low solubility in hydrophilic fluids. Thus, we prepared a water-soluble nanomicellar formulation of CTZ (nCTZ) and tested on the human breast cancer cell line MCF-7 biology.CTZ was nanoencapsulated in tween 80 micelles, which generated nanomicelles of, approximately, 17 nm of diameter. MCF-7 cells were treated with nCTZ and unencapsulated DMSO-solubilized drug (sCTZ) was used for comparison. After treatment, the cells were evaluated in terms of metabolism, proliferation, survival and structure. We found that nCTZ was more efficient than sCTZ at inhibiting glycolytic and other cytosolic and mitochondrial enzymes. Moreover, this increased activity was also observed for lactate production, intracellular ATP content, ROS production and antioxidant potential. As a consequence, nCTZ-treated MCF-7 cells displayed alterations to the plasma membrane, mitochondria and the nucleus. Finally, nCTZ induced both apoptosis and necrosis in MCF-7 cells.MCF-7 cells are more sensible to nCTZ than to sCTZ. This was especially evident on regard to antioxidant potential, which is an important cell defense against drugs that affect cell metabolism. Moreover, this water-soluble formulation of CTZ strengths its potential use as an anticancer medicine