A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance

Evolutionary Dynamics of Multigene Families in Triportheus (Characiformes, Triportheidae): A Transposon Mediated Mechanism?

Triportheus (Characiformes, Triportheidae) is a freshwater fish genus with 18 valid species. These fishes are widely distributed in the major river drainages of South America, having commercial importance in the fishing market, mainly in the Amazon basin. This genus has diverged recently in a complex process of speciation carried out in different river basins. The use of repetitive sequences is suitable to trace the genomic reorganizations occured along the speciation process. In this work, the 5S rDNA multigene family has been characterized at molecular and phylogenetic level. The results showed that other multigene family has been found within the non-transcribed spacer (NTS): the U1 snRNA gene. Double-FISH with 5S and U1 probes were also performed, confirming the close linkage between these two multigene families. Moreover, evidences of different transposable elements (TE) were detected within the spacer, thus suggesting a transposon-mediated mechanism of 5S-U1 evolutionary pathway in this genus. Phylogenetic analysis demonstrated a species-specific grouping, except for Triportheus pantanensis, Triportheus aff. rotundatus and Triportheus trifurcatus. The evolutionary model of the 5S rDNA in Triportheus species has been discussed. In addition, the results suggest new clues for the speciation and evolutionary trend in these species, which could be suitable to use in other Characiformes species

Hidden musculoskeletal involvement in inflammatory bowel disease: a multicenter ultrasound study

BACKGROUND: Inflammatory bowel diseases are associated with a variety of extra-intestinal manifestations. The most frequent of these is joint involvement, which affects 16-33 % of IBD patients. Our aim was to evaluate the ultrasound prevalence of sub-clinical joint and entheseal involvement in patients with IBD without musculoskeletal symptoms, and to correlate the US findings with clinical and laboratory variables. METHODS: We recorded the clinical and laboratory data of 76 patients with IBD, 20 patients with spondyloarthritis (SpA) and 45 healthy controls at three rheumatology centers. All of the IBD patients and healthy controls were clinically examined by a rheumatologist in order to confirm the absence of musculoskeletal symptoms, and all of the subjects underwent grey-scale (GS) and power Doppler (PD) US examinations of the second and third metacarpophalangeal joints, knees and lower limbs in order to detect joint or entheseal abnormalities. RESULTS: A total of 1410 entheseal sites and 1410 joints were evaluated by US. Of the 76 patients with IBD, 64 (84.1 %) had at least one GS entheseal abnormality, and 11 (13.9 %) had more than one PD-positive entheseal site; 32 (42.1 %) showed sub-clinical joint involvement. There was a significant difference between the IBD patients and healthy controls in terms of global entheseal, PD-positive entheseal, and joint involvement (p < 0.0001), but no difference between the IBD and SpA patients. Anti-neutrophil cytoplasmic antibodies predicted entheseal involvement in patients with IBD (OR 6.031; p = 0.015). CONCLUSIONS: The prevalence of sub-clinical joint and entheseal involvement was higher in IBD patients than healthy controls, but there was no difference between the IBD and SpA patients

Measurement of the branching ratio for beta-delayed alpha decay of 16N

While the 12C(a,g)16O reaction plays a central role in nuclear astrophysics, the cross section at energies relevant to hydrostatic helium burning is too small to be directly measured in the laboratory. The beta-delayed alpha spectrum of 16N can be used to constrain the extrapolation of the E1 component of the S-factor; however, with this approach the resulting S-factor becomes strongly correlated with the assumed beta-alpha branching ratio. We have remeasured the beta-alpha branching ratio by implanting 16N ions in a segmented Si detector and counting the number of beta-alpha decays relative to the number of implantations. Our result, 1.49(5)e-5, represents a 24% increase compared to the accepted value and implies an increase of 14% in the extrapolated S-factor

Presence of antibody anti-Corynebacterium pseudotuberculosis in sheep in Dormentes state fo Pernambuco, Brazil.

The Northeast has the largest Brazilian herd of goat sand sheep. Approximately 60% of these animais are located on small farms, on this fact, are the major health problems of which still exist in this region

Plataforma de monitorização e suporte à decisão de doentes críticos

A situação complexa dos doentes críticos e a quantidade de dados disponíveis dificultam a obtenção de conhecimento profícuo para a decisão. Acrescendo o facto de nas Unidades de Cuidados Intensivos (UCI) ainda existir um elevado número de dados em papel, o decisor não consegue interpretar corretamente e em tempo útil toda a informação adquirida. Neste contexto, o fator humano pode provocar erros no processo de tomada de decisão (PTD), uma vez que, normalmente, não há tempo suficiente para analisar corretamente a situação clínica do doente. Para facilitar a aquisição de conhecimento e suportar o PTD por parte dos profissionais da UCI, foi desenvolvida uma plataforma global que, de entre as várias funcionalidades, permite um acompanhamento do doente e a previsão de eventos futuros de uma forma contínua e em tempo real, apresentando novos conhecimentos que podem contribuir de forma significativa para a melhoria da situação clínica de um doente.The complex situation of critical patients and the amount of data available in Intensive Care Units (ICU) makes difficult to obtain useful knowledge to the decision. Adding the fact that in ICU there is a large number of data on paper the decision maker cannot interpret correctly and in short time all the information acquired. In this context the human factor can cause errors in decision-making process (DMP), because normally the intensivist does not have enough time to properly analyse the clinical condition of the patient. To facilitate the acquisition of knowledge and support the ICU decision process by their professionals, a global platform was developed. Among the various features, this platform allows patient monitoring and forecasting future events continuously and in real time, presenting whenever is possible new knowledge which can contribute significantly to the improvement of the clinical status of a patient

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%