Avaliação do curso de gerenciamento online na perspectiva dos egressos

RESUMO Objetivo Avaliar curso online na perspectiva do egresso e verificar a relação entre variáveis. Método Estudo quantitativo, descritivo e exploratório, aplicado aos participantes no final de três versões de um curso de atualização onlinena temática de Gerenciamento em Enfermagem. Resultados Os índices de satisfação nas três categorias elencadas, em três anos, apresentaram resultados acima de 75,0%. Os coeficientes obtidos indicaram alta consistência do questionário. Considerando o índice total, a categoria Desempenho do tutor foi a de índice mais alto. Fortes associações entre Autoavaliação e Desempenho do tutor, Autoavaliação e Programa do curso e Desempenho do tutor e Programa do curso foram identificadas. Não houve associação entre as três categorias referidas com as demais variáveis do estudo. Conclusão Os egressos demonstraram satisfação com o curso, que favoreceu a interação e a promoção do conhecimento coletivo no gerenciamento em enfermagem. Foram reconhecidos, também, aspectos que carecem de melhorias, com destaque à capacitação do tutor para mediar discussões e estimular o envolvimento do estudante ao longo do curso

Summary of data reported to CDC's national automated biosurveillance system, 2008

<p>Abstract</p> <p>Background</p> <p>BioSense is the US national automated biosurveillance system. Data regarding chief complaints and diagnoses are automatically pre-processed into 11 broader syndromes (e.g., respiratory) and 78 narrower sub-syndromes (e.g., asthma). The objectives of this report are to present the types of illness and injury that can be studied using these data and the frequency of visits for the syndromes and sub-syndromes in the various data types; this information will facilitate use of the system and comparison with other systems.</p> <p>Methods</p> <p>For each major data source, we summarized information on the facilities, timeliness, patient demographics, and rates of visits for each syndrome and sub-syndrome.</p> <p>Results</p> <p>In 2008, the primary data sources were the 333 US Department of Defense, 770 US Veterans Affairs, and 532 civilian hospital emergency department facilities. Median times from patient visit to record receipt at CDC were 2.2 days, 2.0 days, and 4 hours for these sources respectively. Among sub-syndromes, we summarize mean 2008 visit rates in 45 infectious disease categories, 11 injury categories, 7 chronic disease categories, and 15 other categories.</p> <p>Conclusions</p> <p>We present a systematic summary of data that is automatically available to public health departments for monitoring and responding to emergencies.</p

Translating upwards: linking the neural and social sciences via neuroeconomics

The social and neural sciences share a common interest in understanding the mechanisms that underlie human behaviour. However, interactions between neuroscience and social science disciplines remain strikingly narrow and tenuous. We illustrate the scope and challenges for such interactions using the paradigmatic example of neuroeconomics. Using quantitative analyses of both its scientific literature and the social networks in its intellectual community, we show that neuroeconomics now reflects a true disciplinary integration, such that research topics and scientific communities with interdisciplinary span exert greater influence on the field. However, our analyses also reveal key structural and intellectual challenges in balancing the goals of neuroscience with those of the social sciences. To address these challenges, we offer a set of prescriptive recommendations for directing future research in neuroeconomics

Decellularized Matrix from Tumorigenic Human Mesenchymal Stem Cells Promotes Neovascularization with Galectin-1 Dependent Endothelial Interaction

BACKGROUND: Acquisition of a blood supply is fundamental for extensive tumor growth. We recently described vascular heterogeneity in tumours derived from cell clones of a human mesenchymal stem cell (hMSC) strain (hMSC-TERT20) immortalized by retroviral vector mediated human telomerase (hTERT) gene expression. Histological analysis showed that cells of the most vascularized tumorigenic clone, -BD11 had a pericyte-like alpha smooth muscle actin (ASMA+) and CD146+ positive phenotype. Upon serum withdrawal in culture, -BD11 cells formed cord-like structures mimicking capillary morphogenesis. In contrast, cells of the poorly tumorigenic clone, -BC8 did not stain for ASMA, tumours were less vascularized and serum withdrawal in culture led to cell death. By exploring the heterogeneity in hMSC-TERT20 clones we aimed to understand molecular mechanisms by which mesenchymal stem cells may promote neovascularization. METHODOLOGY/PRINCIPAL FINDINGS: Quantitative qRT-PCR analysis revealed similar mRNA levels for genes encoding the angiogenic cytokines VEGF and Angiopoietin-1 in both clones. However, clone-BD11 produced a denser extracellular matrix that supported stable ex vivo capillary morphogenesis of human endothelial cells and promoted in vivo neovascularization. Proteomic characterization of the -BD11 decellularized matrix identified 50 extracellular angiogenic proteins, including galectin-1. siRNA knock down of galectin-1 expression abrogated the ex vivo interaction between decellularized -BD11 matrix and endothelial cells. More stable shRNA knock down of galectin-1 expression did not prevent -BD11 tumorigenesis, but greatly reduced endothelial migration into -BD11 cell xenografts. CONCLUSIONS: Decellularized hMSC matrix had significant angiogenic potential with at least 50 angiogenic cell surface and extracellular proteins, implicated in attracting endothelial cells, their adhesion and activation to form tubular structures. hMSC -BD11 surface galectin-1 expression was required to bring about matrix-endothelial interactions and for xenografted hMSC -BD11 cells to optimally recruit host vasculature

Combined Tevatron upper limit on gg->H->W+W- and constraints on the Higgs boson mass in fourth-generation fermion models

Report number: FERMILAB-PUB-10-125-EWe combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg->H->W+W- in p=pbar collisions at the Fermilab Tevatron Collider at sqrt{s}=1.96 TeV. With 4.8 fb-1 of integrated luminosity analyzed at CDF and 5.4 fb-1 at D0, the 95% Confidence Level upper limit on \sigma(gg->H) x B(H->W+W-) is 1.75 pb at m_H=120 GeV, 0.38 pb at m_H=165 GeV, and 0.83 pb at m_H=200 GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% Confidence Level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.We combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg→H→W+W- in pp̅ collisions at the Fermilab Tevatron Collider at √s=1.96  TeV. With 4.8  fb-1 of integrated luminosity analyzed at CDF and 5.4  fb-1 at D0, the 95% confidence level upper limit on σ(gg→H)×B(H→W+W-) is 1.75 pb at mH=120  GeV, 0.38 pb at mH=165  GeV, and 0.83 pb at mH=200  GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% confidence level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.Peer reviewe

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases