Pulse wave velocity distribution in a cohort study: from arterial stiffness to early vascular aging

BACKGROUND: By contrast with other southern European people, north Portuguese population registers an especially high prevalence of hypertension and stroke incidence. We designed a cohort study to identify individuals presenting accelerated and premature arterial aging in the Portuguese population. METHOD: Pulse wave velocity (PWV) was measured in randomly sampled population dwellers aged 18-96 years from northern Portugal, and used as a marker of early vascular aging (EVA). Of the 3038 individuals enrolled, 2542 completed the evaluation. RESULTS: Mean PWV value for the entire population was 8.4?m/s (men: 8.6?m/s; women: 8.2?m/s; P??10?m/s). Logistic regression models indicated gender differences concerning the risk of developing large artery damage, with women having the same odds of PWV above 10?m/s 10 years later than men. CONCLUSION: The population PWV values were higher than expected in a low cardiovascular risk area (Portugal). High prevalence rates of EVA and noteworthy large artery damage in young ages were found.

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Study of the retinoic acid regulated genes in the rodent hypothalamus controlling growth and appetite and the potential for the epigenetic control

Dissertação de mestrado em Bioquímica (área de especialização em Biomedicina)

The internet in young people's everyday life: listening to portuguese teens' voices

[Excerto] Children and young people today go about their lives in an increasingly mediatized fashion. Their daily lives are inhabited by a variety of media, ranging from the so-called new media to the more traditional ones, which have an impact on how they perceive, get to kno,v and represent the world, how they interact with others, how they build their identity, and how they study, have fun and organize their daily lives. The media ecosystem, namely the digit.:tl environments, opened up opportunities to communicate, participate, create and produce information. Apparently, children and young people now have more means and opportunities at their disposal to express and share their ideas, interests and opinions, but are they actually taking advantage of such potential? \'(that uses are they making of these means? Does the Internet, in fact, enable the younger generations to create a new communication culture of expression and participation (...)?

Introduction [to Contact force models for multibody dynamics]

"Series: Solid mechanics and its applications, vol. 226"

Pure elastic contact force models

"Series: Solid mechanics and its applications, vol. 226"

Dissipative contact force models

"Series: Solid mechanics and its applications, vol. 226"

Contact force models for multibody dynamics

"Series: Solid mechanics and its applications, vol. 226"

An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

Optimização do processo de recolha de resíduos: desenvolvimento de ferramentas de investigação operacional para o problema de orientação de equipas com multi-restrições

Tese de Doutoramento em Engenharia Industrial e de Sistemas.