PCR detection of multiple human herpesvirus DNA in saliva from HIV-infected individuals in Teresina, State of Piauí, Brazil

INTRODUCTION: Human herpesviruses are frequently associated with orofacial diseases in humans (HSV-1, EBV, CMV and HHV-8), some can also cause systemic disease (CMV and HHV-8). The transmission of these viruses occurs by contact with infected secretions, especially saliva. Human immunodeficiency virus infection is associated with an increased risk of HHVs and related diseases. METHODS: This work aimed to detect HSV-1, EBV, CMV and HHV-8 DNA in saliva of HIV-infected patients from Teresina, northeast Brazil, by PCR and compare these findings with age and sex matched HIV-seronegative individuals. RESULTS: No difference in prevalence was verified between HHV detection in the saliva of HIV-seropositive individuals and controls. The individual frequencies of these viruses in these two populations were different. HIV seropositivity correlated positively with the presence of CMV (OR: 18.2, p= 0.00032) and EBV (OR: 3.44, p= 0.0081). No association between CD4 counts and the prevalence of HHVs in the saliva was observed; however, a strong association was determined between seropositivity and the presence of multiple HHV DNAs in saliva (OR: 4.83, p = 0.0028). CONCLUSIONS: These findings suggest the asymptomatic salivary shedding of HHVs is a common event between HIV-seropositive and seronegative individuals from Teresina, Piauí, Brazil, and, especially for HIV-seropositive patients, saliva is a risk factor for the acquisition/transmission of multiple HHVs.

Challenge in the management of infective endocarditis with multiple valvular involvement

We describe the case of a 41-year-old man with congenital heart disease and infective endocarditis (IE), who presented multiple vegetations attached to the pulmonary, mitral, and aortic valves. Three valve replacements were performed, but the patient developed an abscess at the mitral-aortic intervalvular fibrosa and died due to sepsis. We briefly discuss the indications for surgery in IE, emphasizing its role in the treatment of uncontrolled infection.

Multiple causes of death related to Chagas' disease in Brazil, 1999 to 2007

INTRODUCTION: Chagas' disease is a major public health problem in Brazil and needs extensive and reliable information to support consistent prevention and control actions. This study describes the most common causes of death associated with deaths related to Chagas' disease (underlying or associated cause of death). METHODS: Mortality data were obtained from the Mortality Information System of the Ministry of Health (approximately 9 million deaths). We analyzed all deaths that occurred in Brazil between 1999 and 2007, where Chagas' disease was mentioned on the death certificate as underlying or associated cause (multiple causes of death). RESULTS: There was a total of 53,930 deaths related to Chagas' disease, 44,543 (82.6%) as underlying cause and 9,387 (17.4%) as associated cause. The main diseases and conditions associated with death by Chagas' disease as underlying cause included direct complications of cardiac involvement, such as conduction disorders/arrhythmias (41.4%) and heart failure (37.7%). Cerebrovascular disease (13.2%), ischemic heart disease (13.2%) and hypertensive diseases (9.3%) were the main underlying causes of deaths in which Chagas' disease was identified as an associated cause. CONCLUSIONS: Cardiovascular diseases were often associated with deaths related to Chagas' disease. Information from multiple causes of death recorded on death certificates allows reconstruction of the natural history of Chagas' disease and suggests preventive and therapeutic potential measures more adequate and specifics.

Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.

Conception and first results of a cross-sectional national study on the demography, disease characteristics and socioeconomics status of the Portuguese patients with multiple sclerosis : the PORT-MS study

RESUMO: Introdução e objetivos: Não existia um estudo multicêntrico que descrevesse as características dos doentes com EM, da doença em si, ou do seu tratamento, em Portugal.Métodos: Doentes McDonald 2010 positivos foram sequencialmente recrutados em 7 centros entre Maio e Novembro 2014. Aplicou-se um Caderno de Recolha de Dados incidindo na demografia, doença, educação e emprego (estudo PORT-MS). Resultados: 561 doentes incluídos. Primeiros sintomas aos 30,2±10,5 anos (RRMS 29,2±10, PPMS 39,4±11,7, p<0,001); diagnóstico 3,2±5,3 anos depois (RRMS 3,0±5,1, PPMS 4,9±2,5, p=0,002); tempo de doença após diagnóstico 9,4±7,2 anos (semelhante RRMS no diagnóstico e PPMS); idade atual 42,9±12,4 anos (grupo RRMS no diagnóstico 42,0±12,1, PPMS 52,5±11,3, p<0,001); EDSS atual 2,5 (RRMS 2.0, PPMS 6.0); proporção feminino:masculino é 2,5:1 (RRMS semelhante, PPMS 1,1:1, p<0,05); no diagnóstico RRMS 90,6%, SPMS 0,9%, PPMS 8,6%; 9,5% dos RRMS encontravam-se em SP na inclusão (nomeadamente os com mais idade no diagnóstico e/ou atualidade ou tempo de doença mais prolongado). PPMS mais frequente em doentes diagnosticados mais tardiamente (p<0,001), onde aumenta também ligeiramente a proporção de mulheres na PPMS. Nas últimas décadas: novos casos mostram estabilidade na proporção de géneros e tipos de doença; idade nos primeiros sintomas e no diagnóstico aumentou ligeiramente, tempo entre eles diminuiu ligeiramente. Proporção sob DMT (Maio 2014): global 84,5%; atualmente RRMS 90,4%; SPMS 70,8%; PPMS 36,8%; progressivas agregadas 48%. Tipo de DMT, amostra global: interferões 56,5%, GA 18,4%, Natalizumab 11,6%, Fingolimod 9,7%. Global: economicamente ativos 61,5%, desemprego 13,5%, 74,1% dos não activos estão reformados por doença. Gravidezes após diagnóstico em 15% mulheres. Casos com história familiar positiva 7,8%. Discussão e conclusões: Incluída cerca de 10% da população portuguesa. Resultados congruentes com dados internacionais. Elevada proporção sob DMT, mesmo EDSS alto e formas progressivas. Terapêuticas de segunda linha sub representadas. Doentes jovens e com doença ligeira com vida económica ativa; restantes essencialmente reformados por doença.---------------- ABSTRACT : Background/aims: In Portugal, there wasn’t a multicentric study on the general characteristics (demography, disease milestones, DMT, socioeconomic status) of Multiple Sclerosis patients. Methods: Patients fulfilling McDonald 2010 criteria were sequentially recruited from May to November 2014 in 7 centers and data was systematically collected. Results: 561 patients included. First symptoms occurred at 30,2±10,5 years-old (RRMS 29,2±10, PPMS 39,4±11,7, p<0,001); diagnosis 3,2±5,3 years later (RRMS 3,0±5,1, PPMS 4,9±2,5, p=0,002); 9,4±7,2 years elapsed since diagnosis (similar for those is RRMS at diagnosis and PPMS); current age 42,9±12,4 years-old (group RRMS at diagnosis 42,0±12,1, PPMS 52,5±11,3, p<0,001); current EDSS 2,5 (RRMS 2.0, PPMS 6.0); females to males 2,5:1 (RRMS similar, PPMS 1,1:1, p<0,05); at diagnosis RRMS 90,6%, SPMS 0,9%, PPMS 8,6%; 9,5% of RRMS reached SP at inclusion (those older at diagnosis, in actuality, or with longer follow-up). PPMS more frequente in patients diagnosed at older ages (p<0,001), also slight increase in females. Along the last decades: new cases have showed stable proportions of gender and disease types; age at first symptoms and diagnosis slightly increased, time between them slightly decreased. Proportion on DMT (May 2014): 84,5% of all; 90,4% of currently in RRMS; 70,8% of SPMS; 36,8% of PPMS; 48% of progressive forms together. Type of DMT, all patients: interferons 56,5%, Glatiramer Acetate 18,4%, Natalizumab 11,6%, Fingolimod 9,7%. Economically active 61,5% of all, unemployment 13,5%, 74,1% of non-active are retired due to disease. Females pregnant after diagnosis 15%. Positive family cases in 7,8%. Discussion/Conclusions: 10% of the national MS population collected. Data generally consistente with international reports. Proportion under DMT relatively high in all disease types, but second line therapies underrepresented. Young patients with mild disease have an active economic life. Those not active are essentially retired due to disease.

Prevalence of intestinal parasites and risk factors forspecific and multiple helminth infections in a remote city of the Brazilian Amazon

Abstract: INTRODUCTION: Few studies have described the risk factors of intestinal parasitic infections in the Amazon. METHODS: A cross-sectional survey was performed in a City of the State of Amazonas (Brazil) to estimate the prevalence of intestinal parasites and determine the risk factors for helminth infections. RESULTS: Ascaris lumbricoides was the most prevalent parasite. The main risk factors determined were: not having a latrine for A. lumbricoides infection; being male and having earth or wood floors for hookworm infection; and being male for multiple helminth infections. CONCLUSIONS: We reported a high prevalence of intestinal parasites and determined some poverty-related risk factors.

Improving the early diagnostic of prostate cancer by multiple biomarker detection with new biosensing devices

Prostate cancer (PCa) is the most common form of cancer in men, in Europe (World Health Organization data). The most recent statistics, in Portuguese territory, confirm this scenario, which states that about 50% of Portuguese men may suffer from prostate cancer and 15% of these will die from this condition. Its early detection is therefore fundamental. This is currently being done by Prostate Specific Antigen (PSA) screening in urine but false positive and negative results are quite often obtained and many patients are sent to unnecessary biopsy procedures. This early detection protocol may be improved, by the development of point-of-care cancer detection devices, not only to PSA but also to other biomarkers recently identified. Thus, the present work aims to screen several biomarkers in cultured human prostate cell lines, serum and urine samples, developing low cost sensors based on new synthetic biomaterials. Biomarkers considered in this study are the following: prostate specific antigen (PSA), annexin A3 (ANXA3), microseminoprotein-beta (MSMB) and sarcosine (SAR). The biomarker recognition may occurs by means of molecularly imprinted polymers (MIP), which are a kind of plastic antibodies, and enzymatic approaches. The growth of a rigid polymer, chemically stable, using the biomarker as a template allows the synthesis of the plastic antibody. MIPs show high sensitivity/selectivity and present much longer stability and much lower price than natural antibodies. This nanostructured material was prepared on a carbon solid. The interaction between the biomarker and the sensing-material produces electrical signals generating quantitative or semi-quantitative data. These devices allow inexpensive and portable detection in point-of-care testing.

The effect of intravenous zoledronic acid on glucocorticoid-induced multiple vertebral fractures in juvenile systemic lupus erythematosus

Glucocorticoids are widely used in the treatment of lupus patients, and adverse effects, which include osteoporosis and associated fractures, are frequent. Treatment of osteoporosis of young patients should be effective and not harmful to bone growth and remodeling. Bisphosphonates are drugs that decrease the incidence of bone fractures, but their use in juvenile patients is still controversial because of their possible side effects on the growing skeleton. However, recently published studies showed that linear growth continued normally after treatment with these drugs, and there was no excessive suppression of bone remodeling or mineralization defects. Zoledronic acid is a new intravenous bisphosphonate that has been approved by the US FDA for use with hypercalcemia of malignancies and might be an effective treatment for postmenopausal osteoporosis. The authors report a case of a young girl with systemic lupus who developed multiple vertebral collapses due to glucocorticoid therapy, and zoledronic acid was used producing significant clinical and densitometric improvement.

Quadratic programming versus second order con programming in portfolio optimization

Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.

Is Modernity Multiple?

Fundação para a Ciência e a Tecnologia (FCT), Fundação Millennium bcp

Implementação de um modelo de geometric semantic genetic programming para aplicação naval

Recaí sob a responsabilidade da Marinha Portuguesa a gestão da Zona Económica Exclusiva de Portugal, assegurando a sua segurança da mesma face a atividades criminosas. Para auxiliar a tarefa, é utilizado o sistema Oversee, utilizado para monitorizar a posição de todas as embarcações presentes na área afeta, permitindo a rápida intervenção da Marinha Portuguesa quando e onde necessário. No entanto, o sistema necessita de transmissões periódicas constantes originadas nas embarcações para operar corretamente – casos as transmissões sejam interrompidas, deliberada ou acidentalmente, o sistema deixa de conseguir localizar embarcações, dificultando a intervenção da Marinha. A fim de colmatar esta falha, é proposto adicionar ao sistema Oversee a capacidade de prever as posições futuras de uma embarcação com base no seu trajeto até à cessação das transmissões. Tendo em conta os grandes volumes de dados gerados pelo sistema (históricos de posições), a área de Inteligência Artificial apresenta uma possível solução para este problema. Atendendo às necessidades de resposta rápida do problema abordado, o algoritmo de Geometric Semantic Genetic Programming baseado em referências de Vanneschi et al. apresenta-se como uma possível solução, tendo já produzido bons resultados em problemas semelhantes. O presente trabalho de tese pretende integrar o algoritmo de Geometric Semantic Genetic Programming desenvolvido com o sistema Oversee, a fim de lhe conceder capacidades preditivas. Adicionalmente, será realizado um processo de análise de desempenho a fim de determinar qual a ideal parametrização do algoritmo. Pretende-se com esta tese fornecer à Marinha Portuguesa uma ferramenta capaz de auxiliar o controlo da Zona Económica Exclusiva Portuguesa, permitindo a correta intervenção da Marinha em casos onde o atual sistema não conseguiria determinar a correta posição da embarcação em questão.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.