A impiedade das críticas ou a consciência da auto-regulação? O processo Casa Pia e o julgamento metajornalístico

(Excerto) Na sua justa e verdadeira atitude, o jornalismo aspira acima de tudo à procura do verdadeiro e do justo. É sua vocação primeira informar, revelar a genuinidade da vida. Mas a informação não existe jamais em si. Ela resulta, segundo Dominique Wolton, de uma construção de homens que tentam compreender o mundo para o dizer a outros homens. A informação funda-se, pois, no pressuposto de um poder, aparentemente exclusivo dos jornalistas: o poder de olhar o mundo e dizer dele o que se espera que todos devam saber. Este poder, que uns designaram por quarto (vigilante dos três poderes fundacionais do Estado democrático- liberal) e que outros3 entenderam sobrepor- se veemente às autoridades executiva, legislativa e judicial, é para Dominique Wolton a prova de que os jornalistas são os grandes vencedores do último meio século.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

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.

Utilização de endoprótese auto-expansível (Stent) introduzida através da artéria femoral para tratamento de dissecção da aorta descendente

OBJETIVO: Apresentar a correção de dissecção da aorta descendente, utilizando stent recoberto com dácron® introduzido através da artéria femoral na sala de hemodinâmica. MÉTODOS: Quatro pacientes foram submetidos à sedação, anestesia local de ambas regiões inguinais e a heparinização sistêmica, com cateter contendo o stent introduzido, através da artéria femoral comum, previamente dissecada, até a aorta descendente no seu terço médio. RESULTADOS: A expansão do stent foi realizada no local onde existia a lesão da íntima, diagnosticada por arteriografia e ecocardiograma. A oclusão da falsa luz foi imediata. O tempo do procedimento foi em média de 1h e 30min. A alta hospitalar ocorreu sem complicações. CONCLUSÃO: Este procedimento poderá proporcionar uma melhora substancial nos resultados do tratamento das dissecções da aorta descendente.

Difference in the in-hospital mortality of unstable angina pectoris between men and women

PURPOSE: To assess differences in the in-hospital mortality (HM) rate between men and women with unstable angina pectoris (UA) according to age, depression of the ST segment, history of previous acute myocardial infarction (AMI), and risk factors for coronary heart disease. METHODS: From October 96 to March 98, 261 patients with UA were selected. Logistic regression models were developed to adjust the association between sex and HM for possible influence of covariables, such as hypertension, diabetes mellitus, dyslipidemia, sedentary lifestyle, smoking, and familial history of early coronary heart disease. RESULTS: HM due to UA was approximately three times higher in women (9.3%; 12/129) than in men (3.0%; 4/132) accounting for a relative risk of 3.07; 95% confidence interval (CI) =1.02-9.27. In logistic regression models, the association between sex and death was not significantly altered when the following parameters were considered: age, depression of the ST segment, history of previous AMI and risk factors for coronary heart disease. The nonadjusted and adjusted odds ratio (OR) for the distinct covariables were 3.28 (CI 95%=1.03-10.45) and 3.14 (CI = 95% = 0.88-11.20), respectively. CONCLUSION: Similarly to AMI, HM in UA is higher in women than in men. Age, risk factors for coronary heart disease, and depression of the ST segment in the electrocardiogram on patients' admission to the hospital did not significantly influence the association between sex and death.

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.

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"

A cumulative risk model of child physical maltreatment potential: findings from a community-based study

"Published online before print November 20, 2015"

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.

Predictive factors of in-hospital mortality and of severe perioperative complications in myocardial revascularization surgery

OBJECTIVE: To investigate preoperative predictive factors of severe perioperative intercurrent events and in-hospital mortality in coronary artery bypass graft (CABG) surgery and to develop specific models of risk prediction for these events, mainly those that can undergo changes in the preoperative period. METHODS: We prospectively studied 453 patients who had undergone CABG. Factors independently associated with the events of interest were determined with multiple logistic regression and Cox proportional hazards regression model. RESULTS: The mortality rate was 11.3% (51/453), and 21.2% of the patients had 1 or more perioperative intercurrent events. In the final model, the following variables remained associated with the risk of intercurrent events: age ³ 70 years, female sex, hospitalization via SUS (Sistema Único de Saúde - the Brazilian public health system), cardiogenic shock, ischemia, and dependence on dialysis. Using multiple logistic regression for in-hospital mortality, the following variables participated in the model of risk prediction: age ³ 70 years, female sex, hospitalization via SUS, diabetes, renal dysfunction, and cardiogenic shock. According to the Cox regression model for death within the 7 days following surgery, the following variables remained associated with mortality: age ³ 70 years, female sex, cardiogenic shock, and hospitalization via SUS. CONCLUSION: The aspects linked to the structure of the Brazilian health system, such as factors of great impact on the results obtained, indicate that the events investigated also depend on factors that do not relate to the patient's intrinsic condition.