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Open access

Maarten Vanhoof, Fernando Reis, Thomas Ploetz and Zbigniew Smoreda

Abstract

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this article, we focus on arguably the most important problem hindering the application of mobile phone data in official statistics: detecting home locations. We argue that current efforts to detect home locations suffer from a blind deployment of criteria to define a place of residence and from limited validation possibilities. We support our argument by analysing the performance of five home detection algorithms (HDAs) that have been applied to a large, French, Call Detailed Record (CDR) data set (~18 million users, five months). Our results show that criteria choice in HDAs influences the detection of home locations for up to about 40% of users, that HDAs perform poorly when compared with a validation data set (resulting in 358-gap), and that their performance is sensitive to the time period and the duration of observation. Based on our findings and experiences, we offer several recommendations for official statistics. If adopted, our recommendations would help ensure more reliable use of mobile phone data vis-à-vis official statistics.

Open access

Evangelos Ioannidis, Takis Merkouris, Li-Chun Zhang, Martin Karlberg, Michalis Petrakos, Fernando Reis and Photis Stavropoulos

Open access

Ana Reis-Mendes, Marisa Alves, Félix Carvalho, Fernando Remião, Maria Lourdes Bastos and Vera Marisa Costa

Abstract

Pixantrone (PIX) is an anticancer drug approved for the treatment of multiple relapsed or refractory aggressive B-cell non-Hodgkin’s lymphoma. It is an aza-anthracenedione synthesized to have the same anticancer activity as its predecessors, anthracyclines (e.g. doxorubicin) and anthracenediones (e.g. mitoxantrone), with lower cardiotoxicity. However, published data regarding its possible cardiotoxicity are scarce. Therefore, this work aimed to assess the potential cytotoxicity of PIX, at clinically relevant concentrations (0.1; 1; and 10 µM) in both non-differentiated and 7-day differentiated H9c2 cells. Cells were exposed to PIX for 48 h and cytotoxicity was evaluated through phase contrast microscopy, Hoescht staining and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) reduction and neutral red (NR) uptake assays. Cytotoxicity was observed in differentiated and non-differentiated H9c2 cells, with detached cells and round cells evidenced by phase contrast microscopy, mainly at the highest concentration tested (10 µM). In the Hoechst staining, PIX 10 µM showed a marked decrease in the number of cells when compared to control but with no signs of nuclear condensation. Furthermore, significant concentration-dependent mitochondrial dysfunction was observed through the MTT reduction assay. The NR assay showed similar results to those obtained in the MTT reduction assay in both differentiated and non-differentiated H9c2 cells. The differentiation state of the cells was not crucial to PIX effects, although PIX toxicity was slightly higher in differentiated H9c2 cells. To the best of our knowledge, this was the first in vitro study performed with PIX in H9c2 cells and it discloses worrying cytotoxicity at clinically relevant concentrations.

Open access

Laura M. L. Carvalho, Fernando M. dos Reis, Ana Lucia Candido, Fernanda F. C. Nunes, Claudia N. Ferreira and Karina B. Gomes

Abstract

Polycystic Ovary Syndrome (PCOS) is characterized by hyperandrogenism, amenorrhea, and polycystic ovaries. This endocrinopathy is associated with many metabolic disorders such as dyslipidemia and insulin resistance, with increased risk of type 2 diabetes mellitus, metabolic syndrome, and cardiovascular complications. Inflammation is likely to play an important role in the promoting these metabolic imbalances, while prothrombotic and pro-oxidative mechanisms further contribute to the cardiovascular risk of these patients. The etiology of PCOS is still not fully understood, but there is evidence of genetic and environmental components. This review aims to discuss some molecular pathways associated with PCOS that could contribute to the better understanding about this syndrome. Recent evidence suggests that intrauterine exposure of female mice to an excess of anti-Müllerian hormone may induce PCOS features in their post-natal life. High cytokine levels and cytokine gene polymorphisms also appear to be associated with the pathophysiology of PCOS. Furthermore, high levels of microparticles may contribute to the altered hemostasis and enhanced inflammation in PCOS. All these mechanisms may be relevant to clarify some aspects of PCOS pathogenesis and inspire new strategies to prevent the syndrome as well as treat its symptoms and mitigate the risk of long-term complications.

Open access

Evangelos Ioannidis, Takis Merkouris, Li-Chun Zhang, Martin Karlberg, Michalis Petrakos, Fernando Reis and Photis Stavropoulos

Abstract

This article considers a modular approach to the design of integrated social surveys. The approach consists of grouping variables into ‘modules’, each of which is then allocated to one or more ‘instruments’. Each instrument is then administered to a random sample of population units, and each sample unit responds to all modules of the instrument. This approach offers a way of designing a system of integrated social surveys that balances the need to limit the cost and the need to obtain sufficient information. The allocation of the modules to instruments draws on the methodology of split questionnaire designs. The composition of the instruments, that is, how the modules are allocated to instruments, and the corresponding sample sizes are obtained as a solution to an optimisation problem. This optimisation involves minimisation of respondent burden and data collection cost, while respecting certain design constraints usually encountered in practice. These constraints may include, for example, the level of precision required and dependencies between the variables. We propose using a random search algorithm to find approximate optimal solutions to this problem. The algorithm is proved to fulfil conditions that ensure convergence to the global optimum and can also produce an efficient design for a split questionnaire.