What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research

Double–blind control of the data manager doesn't have any impact on data entry reliability and should be considered as an avoidable cost

<p>Abstract</p> <p>Background</p> <p>Database systems have been developed to store data from large medical trials and survey studies. However, a reliable data storage system does not guarantee data entering reliability.</p> <p>We aimed to evaluate if double-blind control of the data manager might have any effect on data-reliability. Our secondary aim was to assess the influence of the inserting position in the insertion-sheet on data-entry accuracy and the effectiveness of electronic controls in identifying data-entering mistakes.</p> <p>Methods</p> <p>A cross-sectional survey and single data-manager data entry.</p> <p>Data from PACMeR_02 survey, which had been conducted within a framework of the SESy-Europe project (PACMeR_01.4), were used as substrate for this study. We analyzed the electronic storage of 6446 medical charts. We structured data insertion in four sequential phases. After each phase, the data stored in the database were tested in order to detect unreliable entries through both computerized and manual random control. Control was provided in a double blind fashion.</p> <p>Results</p> <p>Double-blind control of the data manager didn't improve data entry reliability. Entries near the end of the insertion sheet were correlated with a larger number of mistakes. Data entry monitoring by electronic-control was statistically more effective than hand-searching of randomly selected medical records.</p> <p>Conclusion</p> <p>Double-blind control of the data manager should be considered an avoidable cost. Electronic-control for monitoring of data-entry reliability is suggested.</p

NMR studies of p7 protein from hepatitis C virus

The p7 protein of hepatitis C virus (HCV) plays an important role in the viral lifecycle. Like other members of the viroporin family of small membrane proteins, the amino acid sequence of p7 is largely conserved over the entire range of genotypes, and it forms ion channels that can be blocked by a number of established channel-blocking compounds. Its characteristics as a membrane protein make it difficult to study by most structural techniques, since it requires the presence of lipids to fold and function properly. Purified p7 can be incorporated into phospholipid bilayers and micelles. Initial solid-state nuclear magnetic resonance (NMR) studies of p7 in 14-O-PC/6-O-PC bicelles indicate that the protein contains helical segments that are tilted approximately 10° and 25° relative to the bilayer normal. A truncated construct corresponding to the second transmembrane domain of p7 is shown to have properties similar to those of the full-length protein, and was used to determine that the helix segment tilted at 10° is in the C-terminal portion of the protein. The addition of the channel blocker amantadine to the full-length protein resulted in selective chemical shift changes, demonstrating that NMR has a potential role in the development of drugs targeted to p7

Altered branching patterns of Purkinje cells in mouse model for cortical development disorder

Disrupted cortical cytoarchitecture in cerebellum is a typical pathology in reeler. Particularly interesting are structural problems at the cellular level: dendritic morphology has important functional implication in signal processing. Here we describe a combinatorial imaging method of synchrotron X-ray microtomography with Golgi staining, which can deliver 3-dimensional(3-D) micro-architectures of Purkinje cell(PC) dendrites, and give access to quantitative information in 3-D geometry. In reeler, we visualized in 3-D geometry the shape alterations of planar PC dendrites (i.e., abnormal 3-D arborization). Despite these alterations, the 3-D quantitative analysis of the branching patterns showed no significant changes of the 77 ± 8° branch angle, whereas the branch segment length strongly increased with large fluctuations, comparing to control. The 3-D fractal dimension of the PCs decreased from 1.723 to 1.254, indicating a significant reduction of dendritic complexity. This study provides insights into etiologies and further potential treatment options for lissencephaly and various neurodevelopmental disorders

A new synaptic player leading to autism risk: Met receptor tyrosine kinase

The validity for assigning disorder risk to an autism spectrum disorder (ASD) candidate gene comes from convergent genetic, clinical, and developmental neurobiology data. Here, we review these lines of evidence from multiple human genetic studies, and non-human primate and mouse experiments that support the conclusion that the MET receptor tyrosine kinase (RTK) functions to influence synapse development in circuits relevant to certain core behavioral domains of ASD. There is association of both common functional alleles and rare copy number variants that impact levels of MET expression in the human cortex. The timing of Met expression is linked to axon terminal outgrowth and synaptogenesis in the developing rodent and primate forebrain, and both in vitro and in vivo studies implicate this RTK in dendritic branching, spine maturation, and excitatory connectivity in the neocortex. This impact can occur in a cell-nonautonomous fashion, emphasizing the unique role that Met plays in specific circuits relevant to ASD

Surgical management of Diabetic foot ulcers: A Tanzanian university teaching hospital experience

\ud \ud Diabetic foot ulcers (DFUs) pose a therapeutic challenge to surgeons, especially in developing countries where health care resources are limited and the vast majority of patients present to health facilities late with advanced foot ulcers. A prospective descriptive study was done at Bugando Medical Centre from February 2008 to January 2010 to describe our experience in the surgical management of DFUs in our local environment and compare with what is known in the literature. Of the total 4238 diabetic patients seen at BMC during the period under study, 136 (3.2%) patients had DFUs. Males outnumbered females by the ratio of 1.2:1. Their mean age was 54.32 years (ranged 21-72years). Thirty-eight (27.9%) patients were newly diagnosed diabetic patients. The majority of patients (95.5%) had type 2 diabetes mellitus. The mean duration of diabetes was 8.2 years while the duration of DFUs was 18.34 weeks. Fourteen (10.3%) patients had previous history of foot ulcers and six (4.4%) patients had previous amputations. The forefoot was commonly affected in 60.3% of cases. Neuropathic ulcers were the most common type of DFUs in 57.4% of cases. Wagner's stage 4 and 5 ulcers were the most prevalent at 29.4% and 23.5% respectively. The majority of patients (72.1%) were treated surgically. Lower limb amputation was the most common surgical procedure performed in 56.7% of cases. The complication rate was (33.5%) and surgical site infection was the most common complication (18.8%). Bacterial profile revealed polymicrobial pattern and Staphylococcus aureus was the most frequent microorganism isolated. All the microorganisms isolated showed high resistance to commonly used antibiotics except for Meropenem and imipenem, which were 100% sensitive each respectively. The mean hospital stay was 36.24 ± 12.62 days (ranged 18-128 days). Mortality rate was 13.2%. Diabetic foot ulceration constitutes a major source of morbidity and mortality among patients with diabetes mellitus at Bugando Medical Centre and is the leading cause of non-traumatic lower limb amputation. A multidisciplinary team approach targeting at good glycaemic control, education on foot care and appropriate footware, control of infection and early surgical intervention is required in order to reduce the morbidity and mortality associated with DFUs. Due to polymicrobial infection and antibiotic resistance, surgical intervention must be concerned

Integrated Assessment of Genomic Correlates of Protein Evolutionary Rate

Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (“meta-features”) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins; other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale

A Mathematical Framework for Protein Structure Comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set