Ejercicio físico y estilo de vida sedentario: consecuencias para la salud

Perhaps the greatest barriers for achieving major advances in public health in the twenty-first century result from the paralysis of the pandemic paradigm or from the widespread inability to envision alternative or new models of thought. Human movement represents a complex behavior that is influenced by personal motivation, health and mobility problems, genetic factors, and social and physical environments in which people live. These factors influence the propensity to engage in sedentary behaviors or in physical activity. However, the biological, social, and environmental pathways leading to sedentary behavior versus physical activity may be different. In addition, the health effects associated with sedentary behavior and physical activity may be the result of different biological mechanisms. Thus, our objective was to discuss the importance of physical exercise on health-related outcomes and the consequences of sedentary lifestyles. Research on sedentary behavior has been growing;however, the evidence for its determinants is relatively sparse. More studies are needed to obtain more conclusive results because it is fundamental to understand these complex relationships related to the practice and the acquisition of active and healthy lifestyles as opposed to a sedentary lifestyle.info:eu-repo/semantics/publishedVersio

Low molecular weight heparins: Structural differentiation by spectroscopic and multivariate approaches

Various branded low molecular weight heparins (LMWHs) have been used for the treatment and prevention of thrombotic for over 20 years. With the introduction of generic LMWHs and the recent events involving heparin contamination, a great deal of effort is being expended in investigating ways of monitoring and regulating this class of complex drugs. in this paper, we present the characterization of different forms of LMWHs, as well as the comparison of 5 enoxaparin copies from different manufactures. the data suggests that, while some of these drugs are structurally comparable, specific analytical methods as well as biological and pharmacological tests may be used to address their similarity, quality and potential interchangeability. the proposed approach may also be useful in comparing biosimilar and branded LMWHs. (C) 2011 Elsevier B.V. All rights reserved.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo, Dept Bioquim, BR-04044020 São Paulo, SP, BrazilUniv Liverpool, Sch Biol Sci, Liverpool L69 7ZB, Merseyside, EnglandLoyola Univ, Med Ctr, Dept Pathol, Maywood, IL 60153 USAUniv Fed Parana, Lab Quim Carboidratos, Dept Bioquim & Biol Mol, BR-81531980 Curitiba, Parana, BrazilUniversidade Federal de São Paulo, Dept Bioquim, BR-04044020 São Paulo, SP, BrazilWeb of Scienc

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

Abstract: Fibromyalgia is a rheumatological disorder that causes chronic pain and other symptomatic conditions such as depression and anxiety. Despite its relevance, the disease still presents a complex diagnosis where the doctor needs to have a correct clinical interpretation of the symptoms. In this context, it is valid to study tools that assist in the screening of this disease, using chemical work techniques such as mass spectroscopy. In this study, an analytical method is proposed to detect individuals with fibromyalgia (n = 20, 10 control samples and 10 samples with fibromyalgia) from blood plasma samples analyzed by mass spectrometry with paper spray ionization and subsequent multivariate classification of the spectral data (unsupervised and supervised), in addition to the treatment of selected variables with possible associations with metabolomics. Exploratory analysis with principal component analysis (PCA) and supervised analysis with successive projections algorithm with linear discriminant analysis (SPA-LDA) showed satisfactory results with 100% accuracy for sample prediction in both groups. This demonstrates that this combination of techniques can be used as a simple, reliable and fast tool in the development of clinical diagnosis of Fibromyalgia

Characterization of MTAP gene expression in breast cancer patients and cell lines

MTAP is a ubiquitously expressed gene important for adenine and methionine salvage. The gene is located at 9p21, a chromosome region often deleted in breast carcinomas, similar to CDKN2A, a recognized tumor suppressor gene. Several research groups have shown that MTAP acts as a tumor suppressor, and some therapeutic approaches were proposed based on a tumors\ub4 MTAP status. We analyzed MTAP and CDKN2A gene (RT-qPCR) and protein (western-blotting) expression in seven breast cancer cell lines and evaluated their promoter methylation patterns to better characterize the contribution of these genes to breast cancer. Cytotoxicity assays with inhibitors of de novo adenine synthesis (5-FU, AZA and MTX) after MTAP gene knockdown showed an increased sensitivity, mainly to 5-FU. MTAP expression was also evaluated in two groups of samples from breast cancer patients, fresh tumors and paired normal breast tissue, and from formalin-fixed paraffin embedded (FFPE) core breast cancer samples diagnosed as Luminal-A tumors and triple negative breast tumors (TNBC). The difference of MTAP expression between fresh tumors and normal tissues was not statistically significant. However, MTAP expression was significantly higher in Luminal-A breast tumors than in TNBC, suggesting the lack of expression in more aggressive breast tumors and the possibility of using the new approaches based on MTAP status in TNB

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