EUS could detect ascites missed by CT scan [4]

published_or_final_versio

Familial aggregation of components of the multiple metabolic syndrome in the Framingham Heart and Offspring Cohorts: Genetic Analysis Workshop Problem 1

BACKGROUND: The multiple metabolic syndrome is defined by a clustering of risk factors for cardiovascular disease. We sought to evaluate the familial correlations of the components of the syndrome using data from the Framingham Heart Study original and offspring cohorts as provided for the Genetic Analysis Workshop 13. Measures of plasma cholesterol (total and HDL), body mass index (BMI), and systolic blood pressure were used from selected calendar years of exams. Familial correlations were calculated using FCOR in S.A.G.E. RESULTS: The sibling correlations were relatively high for all measures and exams, from 0.17 for systolic blood pressure to 0.27 for HDL cholesterol. The parent-child correlations were very similar, except for systolic blood pressure. The avuncular correlations were much smaller and the cousin correlations were even smaller. For HDL cholesterol the avuncular correlation was half the sibling correlation and the cousin correlation was half that again. Spousal correlations ranged from 0.07 for systolic blood pressure to 0.34 for BMI. Correlations were somewhat lower from 1984 to 1987 examinations than from 1971 to 1975 examinations, except for spousal correlations for systolic blood pressure and BMI. CONCLUSION: The results of the family pair correlations are suggestive of genetic determinants of lipid levels and BMI. These components have been shown to be predictive of cardiovascular disease as well as diabetes. Genes in common with each of the components might also influence development of cardiovascular disease and diabetes, both complex diseases

Preventing Advanced Persistent Threats in Complex Control Networks

An Advanced Persistent Threat (APT) is an emerging attack against Industrial Control and Automation Systems, that is executed over a long period of time and is difficult to detect. In this context, graph theory can be applied to model the interaction among nodes and the complex attacks affecting them, as well as to design recovery techniques that ensure the survivability of the network. Accordingly, we leverage a decision model to study how a set of hierarchically selected nodes can collaborate to detect an APT within the network, concerning the presence of changes in its topology. Moreover, we implement a response service based on redundant links that dynamically uses a secret sharing scheme and applies a flexible routing protocol depending on the severity of the attack. The ultimate goal is twofold: ensuring the reachability between nodes despite the changes and preventing the path followed by messages from being discovered.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Consecutive treatment with phytase and arazyme influence protein hydrolysis of soybean meal

Soybean meal (SBM) is the main protein supplement used in animal feed worldwide. The degree of hydrolysis (DH) of SBM treated with two enzymes viz. phytase and arazyme was investigated for the first time in this study. The DH of SBM in the treatment with arazyme increased significantly as compared to the control without enzyme application. About 1.5-times and 10-fold higher DH were observed in phytase treatment when compared to the control treatments containing no enzyme. At the end of 24 h, enzymatic hydrolysis was done through consecutive treatment with 0.5% (w/v) phytase and 0.02% (w/v) arazyme, and the protein in the hydrolysate were mostly degraded free amino acids and peptides (<6 KDa) when SDS-PAGE and fast protein liquid chromatography (FPLC) techniques used. Free amino acids contents of the soybean meal treated with phytase-arazyme increased by 2 to 14 fold as compared to products without enzyme. These results suggested that soybean meal proteins continuously treated with phytase and arazyme can be used as commercial feed additive for accelerated livestock growth.Key words: Soybean meal, phytase, arazyme, hydrolysis

Triggering Cell Stress and Death Using Conventional UV Laser Confocal Microscopy.

Using a standard confocal setup, a UV ablation method can be utilized to selectively induce cellular injury and to visualize single-cell responses and cell-cell interactions in the CNS in real-time. Previously, studying these cell-specific responses after injury often required complicated setups or the transfer of cells or animals into different, non-physiological environments, confounding immediate and short-term analysis. For example, drug-mediated ablation approaches often lack the specificity that is required to study single-cell responses and immediate cell-cell interactions. Similarly, while high-power pulsed laser ablation approaches provide very good control and tissue penetration, they require specialized equipment that can complicate real-time visualization of cellular responses. The refined UV laser ablation approach described here allows researchers to stress or kill an individual cell in a dose- and time-dependent manner using a conventional confocal microscope equipped with a 405-nm laser. The method was applied to selectively ablate a single neuron within a dense network of surrounding cells in the zebrafish spinal cord. This approach revealed a dose-dependent response of the ablated neurons, causing the fragmentation of cellular bodies and anterograde degeneration along the axon within minutes to hours. This method allows researchers to study the fate of an individual dying cell and, importantly, the instant response of cells-such as microglia and astrocytes-surrounding the ablation site

Return Visit Admissions May Not Indicate Quality of Emergency Department Care for Children

ObjectiveThe objective was to test the hypothesis that in‐hospital outcomes are worse among children admitted during a return ED visit than among those admitted during an index ED visit.MethodsThis was a retrospective analysis of ED visits by children age 0 to 17 to hospitals in Florida and New York in 2013. Children hospitalized during an ED return visit within 7 days were classified as “ED return admissions” (discharged at ED index visit and admitted at return visit) or “readmissions” (admission at both ED index and return visits). In‐hospital outcomes for ED return admissions and readmissions were compared to “index admissions without return admission” (admitted at ED index visit without 7‐day return visit admission).ResultsAmong 1,886,053 index ED visits to 321 hospitals, 75,437 were index admissions without return admission, 7,561 were ED return admissions, and 1,333 were readmissions. ED return admissions had lower intensive care unit admission rates (11.0% vs. 13.6%; adjusted odds ratio = 0.78; 95% confidence interval [CI] = 0.71 to 0.85), longer length of stay (3.51 days vs. 3.38 days; difference = 0.13 days; incidence rate ratio = 1.04; 95% CI = 1.02 to 1.07), but no difference in mean hospital costs (($7,138 vs.$7,331; difference = –$193; 95$479 to $93) compared to index admissions without return admission.ConclusionsCompared with children who experienced index admissions without return admission, children who are initially discharged from the ED who then have a return visit admission had lower severity and similar cost, suggesting that ED return visit admissions do not involve worse outcomes than do index admissions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142896/1/acem13324_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142896/2/acem13324.pd

Sparse, continuous policy representations for uniform online bin packing via regression of interpolants

Online bin packing is a classic optimisation problem, widely tackled by heuristic methods. In addition to human-designed heuristic packing policies (e.g. first- or best- fit), there has been interest over the last decade in the automatic generation of policies. One of the main limitations of some previously-used policy representations is the trade-off between locality and granularity in the associated search space. In this article, we adopt an interpolation-based representation which has the jointly-desirable properties of being sparse and continuous (i.e. exhibits good genotype-to-phenotype locality). In contrast to previous approaches, the policy space is searchable via real-valued optimization methods. Packing policies using five different interpolation methods are comprehensively compared against a range of existing methods from the literature, and it is determined that the proposed method scales to larger instances than those in the literature