Potentially fatal tricuspid valve aspergilloma detected after laparoscopic abdominal surgery

Fungal endocarditis accounts for 1.3-6% of all cases of infective endocarditis. The most common causative organism is Candida, followed by Aspergillus and other mould fungi. Aspergillus endocarditis is usually associated with high morbidity and mortality. Establishing a definitive and timely diagnosis remains difficult and there are many reports of undetected aspergillomas leading to fatalities in the perioperative period. We present a case report of preoperatively undiagnosed large mobile tricuspid valve aspergilloma obstructing the right ventricular inlet, diagnosed incidentally on the second postoperative day after laparoscopic pancreatic abscess drainage. The patient was successfully managed with emergency open-heart surgery and systemic antifungal agents in the postoperative period.Keywords: Infective endocarditis, aspergilloma, tricuspid valu

A framework for integrating sustainability estimation with concepts of rules of building measurement

BIM promises improvement in project delivery efficiencies such as reduction in costs and errors and timely completion. Benefits are also expected in sustainable construction aspect with research efforts being extended to sustainable design and assessment. These efforts are still been explored for the purposes of unifying quantification methodologies, the standardisation of system boundaries, terms of references and sustainability measures. Embodied energy and CO2 are two common measures that have been widely used in the construction sector. Although a number calculation system exists, they are not useful to the iterations that occur at the early stages of the project life cycle. At the procurement stage, professionals often rely on schedules and bill of quantities with no reference to sustainability credentials. It is therefore important to integrate sustainability measure with concepts in standard measurement methods. As such, we propose a framework to integrate sustainability credential with the concepts in rule of building measurement. We conclude that this framework can be applicable to any rule of building measurement and it is implementable in a computer programmable environment

Discriminative Localized Sparse Representations for Breast Cancer Screening

Breast cancer is the most common cancer among women both in developed and developing countries. Early detection and diagnosis of breast cancer may reduce its mortality and improve the quality of life. Computer-aided detection (CADx) and computer-aided diagnosis (CAD) techniques have shown promise for reducing the burden of human expert reading and improve the accuracy and reproducibility of results. Sparse analysis techniques have produced relevant results for representing and recognizing imaging patterns. In this work we propose a method for Label Consistent Spatially Localized Ensemble Sparse Analysis (LC-SLESA). In this work we apply dictionary learning to our block based sparse analysis method to classify breast lesions as benign or malignant. The performance of our method in conjunction with LC-KSVD dictionary learning is evaluated using 10-, 20-, and 30-fold cross validation on the MIAS dataset. Our results indicate that the proposed sparse analyses may be a useful component for breast cancer screening applications

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. © 2014 Das et al

Justice and Corporate Governance: New Insights from Rawlsian Social Contract and Sen’s Capabilities Approach

By considering what we identify as a problem inherent in the ‘nature of the firm’—the risk of abuse of authority—we propound the conception of a social contract theory of the firm which is truly Rawlsian in its inspiration. Hence, we link the social contract theory of the firm (justice at firm’s level) with the general theory of justice (justice at society’s level). Through this path, we enter the debate about whether firms can be part of Rawlsian theory of justice showing that corporate governance principles enter the “basic structure.” Finally, we concur with Sen’s aim to broaden the realm of social justice beyond what he calls the ‘transcendental institutional perfectionism’ of Rawls’ theory. We maintain the contractarian approach to justice but introduce Sen’s capability concept as an element of the constitutional and post-constitutional contract model of institutions with special reference to corporate governance. Accordingly, rights over primary goods and capabilities are (constitutionally) granted by the basic institutions of society, but many capabilities have to be turned into the functionings of many stakeholders through the operation of firms understood as post-constitutional institutional domains. The constitutional contract on the distribution of primary goods and capabilities should then shape the principles of corporate governance so that at post-constitutional level anyone may achieve her/his functionings in the corporate domain by exercising such capabilities. In the absence of such a condition, post-constitutional contracts would distort the process that descends from constitutional rights and capabilities toward social outcomes

Complete Genome Sequence of the N2-Fixing Broad Host Range Endophyte Klebsiella pneumoniae 342 and Virulence Predictions Verified in Mice

We report here the sequencing and analysis of the genome of the nitrogen-fixing endophyte, Klebsiella pneumoniae 342. Although K. pneumoniae 342 is a member of the enteric bacteria, it serves as a model for studies of endophytic, plant-bacterial associations due to its efficient colonization of plant tissues (including maize and wheat, two of the most important crops in the world), while maintaining a mutualistic relationship that encompasses supplying organic nitrogen to the host plant. Genomic analysis examined K. pneumoniae 342 for the presence of previously identified genes from other bacteria involved in colonization of, or growth in, plants. From this set, approximately one-third were identified in K. pneumoniae 342, suggesting additional factors most likely contribute to its endophytic lifestyle. Comparative genome analyses were used to provide new insights into this question. Results included the identification of metabolic pathways and other features devoted to processing plant-derived cellulosic and aromatic compounds, and a robust complement of transport genes (15.4%), one of the highest percentages in bacterial genomes sequenced. Although virulence and antibiotic resistance genes were predicted, experiments conducted using mouse models showed pathogenicity to be attenuated in this strain. Comparative genomic analyses with the presumed human pathogen K. pneumoniae MGH78578 revealed that MGH78578 apparently cannot fix nitrogen, and the distribution of genes essential to surface attachment, secretion, transport, and regulation and signaling varied between each genome, which may indicate critical divergences between the strains that influence their preferred host ranges and lifestyles (endophytic plant associations for K. pneumoniae 342 and presumably human pathogenesis for MGH78578). Little genome information is available concerning endophytic bacteria. The K. pneumoniae 342 genome will drive new research into this less-understood, but important category of bacterial-plant host relationships, which could ultimately enhance growth and nutrition of important agricultural crops and development of plant-derived products and biofuels

Understanding atmospheric organic aerosols via factor analysis of aerosol mass spectrometry: a review

Organic species are an important but poorly characterized constituent of airborne particulate matter. A quantitative understanding of the organic fraction of particles (organic aerosol, OA) is necessary to reduce some of the largest uncertainties that confound the assessment of the radiative forcing of climate and air quality management policies. In recent years, aerosol mass spectrometry has been increasingly relied upon for highly time-resolved characterization of OA chemistry and for elucidation of aerosol sources and lifecycle processes. Aerodyne aerosol mass spectrometers (AMS) are particularly widely used, because of their ability to quantitatively characterize the size-resolved composition of submicron particles (PM1). AMS report the bulk composition and temporal variations of OA in the form of ensemble mass spectra (MS) acquired over short time intervals. Because each MS represents the linear superposition of the spectra of individual components weighed by their concentrations, multivariate factor analysis of the MS matrix has proved effective at retrieving OA factors that offer a quantitative and simplified description of the thousands of individual organic species. The sum of the factors accounts for nearly 100% of the OA mass and each individual factor typically corresponds to a large group of OA constituents with similar chemical composition and temporal behavior that are characteristic of different sources and/or atmospheric processes. The application of this technique in aerosol mass spectrometry has grown rapidly in the last six years. Here we review multivariate factor analysis techniques applied to AMS and other aerosol mass spectrometers, and summarize key findings from field observations. Results that provide valuable information about aerosol sources and, in particular, secondary OA evolution on regional and global scales are highlighted. Advanced methods, for example a-priori constraints on factor mass spectra and the application of factor analysis to combined aerosol and gas phase data are discussed. Integrated analysis of worldwide OA factors is used to present a holistic regional and global description of OA. Finally, different ways in which OA factors can constrain global and regional models are discussed