A pig model of acute Staphylococcus aureus induced pyemia

<p>Abstract</p> <p>Background</p> <p>Sepsis caused by <it>Staphylococcus aureus </it>constitutes an important cause of morbidity and mortality in humans, and the incidence of this disease-entity is increasing. In this paper we describe the initial microbial dynamics and lesions in pigs experimentally infected with <it>S. aureus</it>, with the aim of mimicking human sepsis and pyemia.</p> <p>Methods</p> <p>The study was conducted in anaesthetized and intravenously inoculated pigs, and was based on bacteriological examination of blood and testing of blood for IL-6 and C-reactive protein. Following killing of the animals and necropsy bacteriological and histological examinations of different organs were performed 4, 5 or 6 h after inoculation.</p> <p>Results</p> <p>Clearance of bacteria from the blood was completed within the first 2 h in some of the pigs and the highest bacterial load was recorded in the lungs as compared to the spleen, liver and bones. This probably was a consequence of both the intravenous route of inoculation and the presence of pulmonary intravascular macrophages. Inoculation of bacteria induced formation of acute microabscesses in the lungs, spleen and liver, but not in the kidneys or bones. No generalized inflammatory response was recorded, i.e. IL-6 was not detected in the blood and C-reactive protein did not increase, probably because of the short time course of the study.</p> <p>Conclusion</p> <p>This study demonstrates the successful induction of acute pyemia (microabscesses), and forms a basis for future experiments that should include inoculation with strains of <it>S. aureus </it>isolated from man and an extension of the timeframe aiming at inducing sepsis, severe sepsis and septic shock.</p

Linguistic feature analysis for protein interaction extraction

<p>Abstract</p> <p>Background</p> <p>The rapid growth of the amount of publicly available reports on biomedical experimental results has recently caused a boost of text mining approaches for protein interaction extraction. Most approaches rely implicitly or explicitly on linguistic, i.e., lexical and syntactic, data extracted from text. However, only few attempts have been made to evaluate the contribution of the different feature types. In this work, we contribute to this evaluation by studying the relative importance of deep syntactic features, i.e., grammatical relations, shallow syntactic features (part-of-speech information) and lexical features. For this purpose, we use a recently proposed approach that uses support vector machines with structured kernels.</p> <p>Results</p> <p>Our results reveal that the contribution of the different feature types varies for the different data sets on which the experiments were conducted. The smaller the training corpus compared to the test data, the more important the role of grammatical relations becomes. Moreover, deep syntactic information based classifiers prove to be more robust on heterogeneous texts where no or only limited common vocabulary is shared.</p> <p>Conclusion</p> <p>Our findings suggest that grammatical relations play an important role in the interaction extraction task. Moreover, the net advantage of adding lexical and shallow syntactic features is small related to the number of added features. This implies that efficient classifiers can be built by using only a small fraction of the features that are typically being used in recent approaches.</p

Transcriptomic comparison of the retina in two mouse models of diabetes

Mouse models of type I diabetes offer the potential to combine genetic approaches with other pharmacological or physiological manipulations to investigate the pathophysiology and treatment of diabetic retinopathy. Type I diabetes is induced in mice through chemical toxins or can arise spontaneously from genetic mutations. Both models are associated with retinal vascular and neuronal changes. Retinal transcriptomic responses in C57BL/6J mice treated with streptozotocin and Ins2Akita/+ were compared after 3 months of hyperglycemia. Specific gene expression changes suggest a neurovascular inflammatory response in diabetic retinopathy. Genes common to the two models may represent the response of the retina to hyperglycemia, while changes unique to each model may represent time-dependent disease progression differences in the various models. Further investigation of the commonalities and differences between mouse models of type I diabetes may define cause and effect events in early diabetic retinopathy disease progression

Kepler eclipsing binary stars. VII. the catalogue of eclipsing binaries found in the entire Kepler data set

The primary Kepler Mission provided nearly continuous monitoring of ~200,000 objects with unprecedented photometric precision. We present the final catalog of eclipsing binary systems within the 105 deg2 Kepler field of view. This release incorporates the full extent of the data from the primary mission (Q0-Q17 Data Release). As a result, new systems have been added, additional false positives have been removed, ephemerides and principal parameters have been recomputed, classifications have been revised to rely on analytical models, and eclipse timing variations have been computed for each system. We identify several classes of systems including those that exhibit tertiary eclipse events, systems that show clear evidence of additional bodies, heartbeat systems, systems with changing eclipse depths, and systems exhibiting only one eclipse event over the duration of the mission. We have updated the period and galactic latitude distribution diagrams and included a catalog completeness evaluation. The total number of identified eclipsing and ellipsoidal binary systems in the Kepler field of view has increased to 2878, 1.3% of all observed Kepler targets

Kepler Eclipsing Binary Stars. Vii. The Catalog Of Eclipsing Binaries Found In The Entire Kepler Data Set

The Kepler mission has provided unprecedented, nearly continuous photometric data of ~200,000 objects in the ~105 deg2 field of view (FOV) from the beginning of science operations in May of 2009 until the loss of the second reaction wheel in May of 2013. The Kepler Eclipsing Binary Catalog contains information including but not limited to ephemerides, stellar parameters, and analytical approximation fits for every known eclipsing binary system in the Kepler FOV. Using target pixel level data collected from Kepler in conjunction with the Kepler Eclipsing Binary Catalog, we identify false positives among eclipsing binaries, i.e., targets that are not eclipsing binaries themselves, but are instead contaminated by eclipsing binary sources nearby on the sky and show eclipsing binary signatures in their light curves. We present methods for identifying these false positives and for extracting new light curves for the true source of the observed binary signal. For each source, we extract three separate light curves for each quarter of available data by optimizing the signal-to-noise ratio, the relative percent eclipse depth, and the flux eclipse depth. We present 289 new eclipsing binaries in the Kepler FOV that were not targets for observation, and these have been added to the catalog