Tableau-based protein substructure search using quadratic programming

<p>Abstract</p> <p>Background</p> <p>Searching for proteins that contain similar substructures is an important task in structural biology. The exact solution of most formulations of this problem, including a recently published method based on tableaux, is too slow for practical use in scanning a large database.</p> <p>Results</p> <p>We developed an improved method for detecting substructural similarities in proteins using tableaux. Tableaux are compared efficiently by solving the quadratic program (QP) corresponding to the quadratic integer program (QIP) formulation of the extraction of maximally-similar tableaux. We compare the accuracy of the method in classifying protein folds with some existing techniques.</p> <p>Conclusion</p> <p>We find that including constraints based on the separation of secondary structure elements increases the accuracy of protein structure search using maximally-similar subtableau extraction, to a level where it has comparable or superior accuracy to existing techniques. We demonstrate that our implementation is able to search a structural database in a matter of hours on a standard PC.</p

Case-study: inorganic pollutants associated with particulate matter from an area near a petrochemical plant

The area of Gela (Sicily, Italy) contains one of the largest petroleum refineries in Europe and also has several oil fields both on land and offshore. This paper discusses how the oil refinery and traffic-related air pollution affect the chemical composition of airborne particulate matter over the town of Gela, usingpine needles and urban road dust as the means of survey. Forty-one samples of pine needles from Pinus halepensis (Mill.) and two composite samples of roadway dust, each subdivided into six size fractions, were analyzed for major and trace elements. Information on the natural or anthropogenic origin of the observed heavy metals was deduced from factor analysis and element distribution maps. Factor analysis was applied to a data set of 20 element concentrations in pine needles and identified three main sources of metals: soil, vehicle traffic, and industrial emissions. The petrochemical plant appears to be associated with raised levels of As, Mo, Ni, S, Se, V, and Zn. Similarly, enhanced Cu, Pb, Pt, Pd, Sb, and partly Zn concentrations are closely associated with traffic. High correlations between Ni and V, As and Se, and Pb and Sb were observed. Element distribution maps, showinga decrease in heavy metal contents immediately farther inland, confirm that local sources play a considerable role in heavy metal pollution. Morphological alterations and accumulation of phenols were observed in sections of Pinus halepensis needles collected from sites with high traffic density and industrial emissions

Development of a System to Invert Eddy-Current Data and Reconstruct Flaws

In this report we describe an approach to the reconstruction of flaws, not merely their detection. This will give us the ability to obtain much more information about the nature of the flaw. By “flaw” we mean virtually any departure of the medium from a standard condition, which is known a priori, such as may be produced not only by a crack but also by conductivity in homogeneities produced by stresses, magnetite build-up, etc. Our approach is very much in the spirit of contemporary work in inverse methods in electromagnetics [1–3] and electromagnetic-geophysical prospecting [4–11].</p

An insight into intestinal mucosal microbiota disruption after stroke

Recent work from our laboratory has provided evidence that indicates selective bacterial translocation from the host gut microbiota to peripheral tissues (i.e. lung) plays a key role in the development of post-stroke infections. Despite this, it is currently unknown whether mucosal bacteria that live on and interact closely with the host intestinal epithelium contribute in regulating bacterial translocation after stroke. Here, we found that the microbial communities within the mucosa of gastrointestinal tract (GIT) were significantly different between sham-operated and post-stroke mice at 24 h following surgery. The differences in microbiota composition were substantial in all sections of the GIT and were significant, even at the phylum level. The main characteristics of the stroke-induced shift in mucosal microbiota composition were an increased abundance of Akkermansia muciniphila and an excessive abundance of clostridial species. Furthermore, we analysed the predicted functional potential of the altered mucosal microbiota induced by stroke using PICRUSt and revealed significant increases in functions associated with infectious diseases, membrane transport and xenobiotic degradation. Our findings revealed stroke induces far-reaching and robust changes to the intestinal mucosal microbiota. A better understanding of the precise molecular events leading up to stroke-induced mucosal microbiota changes may represent novel therapy targets to improve patient outcomes