Presentations: from Kac-Moody groups to profinite and back

We go back and forth between, on the one hand, presentations of arithmetic and Kac-Moody groups and, on the other hand, presentations of profinite groups, deducing along the way new results on both

Development of bile duct bezoars following cholecystectomy caused by choledochoduodenal fistula formation: a case report

BACKGROUND: The formation of bile duct bezoars is a rare event. Its occurrence when there is no history of choledochoenteric anastomosis or duodenal diverticulum constitutes an extremely scarce finding. CASE PRESENTATION: We present a case of obstructive jaundice, caused by the concretion of enteric material (bezoars) in the common bile duct following choledochoduodenal fistula development. Six years after cholecystectomy, a 60-year-old female presented with abdominal pain and jaundice. Endoscopic retrograde cholangiopancreatography demonstrated multiple filling defects in her biliary tract. The size of the obstructing objects necessitated surgical retrieval of the stones. A histological assessment of the objects revealed fibrinoid materials with some cellular debris. Post-operative T-tube cholangiography (9 days after the operation) illustrated an open bile duct without any filling defects. Surprisingly, a relatively long choledochoduodenal fistula was detected. The fistula formation was assumed to have led to the development of the bile duct bezoar. CONCLUSION: Bezoar formation within the bile duct should be taken into consideration as a differential diagnosis, which can alter treatment modalities from surgery to less invasive methods such as more intra-ERCP efforts. Suspicions of the presence of bezoars are strengthened by the detection of a biliary enteric fistula through endoscopic retrograde cholangiopancreatography. Furthermore, patients at a higher risk of fistula formation should undergo a thorough ERCP in case there is a biliodigestive fistula having developed spontaneously

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

The Servant Leadership Survey: Development and Validation of a Multidimensional Measure

Purpose: The purpose of this paper is to describe the development and validation of a multi-dimensional instrument to measure servant leadership. Design/Methodology/Approach Based on an extensive literature review and expert judgment, 99 items were formulated. In three steps, using eight samples totaling 1571 persons from The Netherlands and the UK with a diverse occupational background, a combined exploratory and confirmatory factor analysis approach was used. This was followed by an analysis of the criterion-related validity. Findings: The final result is an eight-dimensional measure of 30 items: the eight dimensions being: standing back, forgiveness, courage, empowerment, accountability, authenticity, humility, and stewardship. The internal consistency of the subscales is good. The results show that the Servant Leadership Survey (SLS) has convergent validity with other leadership measures, and also adds unique elements to the leadership field. Evidence for criterion-related validity came from studies relating the eight dimensions to well-being and performance. Implications: With this survey, a valid and reliable instrument to measure the essential elements of servant leadership has been introduced. Originality/Value The SLS is the first measure where the underlying factor structure was developed and confirmed across several field studies in two countries. It can be used in future studies to test the underlying premises of servant leadership theory. The SLS provides a clear picture of the key servant leadership qualities and shows where improvements can be made on the individual and organizational level; as such, it may also offer a valuable starting point for training and leadership development

A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles

<p>Abstract</p> <p>Background</p> <p>The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI) and matrix assisted laser desorption (MALDI) time-of-flight (TOF) mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compound's intensity either discretely by positional (mass to charge ratio) clustering or through each compounds' own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model.</p> <p>Results</p> <p>In the present study a novel semi-parametric approach has been developed to distinguish urinary metabolic profiles in a group of traumatic patients from those of a control group consisting of normal individuals. Data sets obtained from the replicates of a single subject were used to develop a functional profile through Dirichlet mixture of beta distribution. This functional profile is flexible enough to accommodate variability of the instrument and the inherent variability of each individual, thus simultaneously addressing different sources of systematic error. To address instrument variability, all data sets were analyzed in replicate, an important issue ignored by most studies in the past. Different model comparisons were performed to select the best model for each subject. The m/z values in the window of the irregular pattern are then further recommended for possible biomarker discovery.</p> <p>Conclusion</p> <p>To the best of our knowledge this is the very first attempt to model the physical process behind the time-of flight mass spectrometry. Most of the state of the art techniques does not take these physical principles in consideration while modeling such data. The proposed modeling process will apply as long as the basic physical principle presented in this paper is valid. Notably we have confined our present work mostly within the modeling aspect. Nevertheless clinical validation of our recommended list of potential biomarkers will be required. Hence, we have termed our modeling approach as a "framework" for further work.</p

SEAS: A System for SEED-Based Pathway Enrichment Analysis

Pathway enrichment analysis represents a key technique for analyzing high-throughput omic data, and it can help to link individual genes or proteins found to be differentially expressed under specific conditions to well-understood biological pathways. We present here a computational tool, SEAS, for pathway enrichment analysis over a given set of genes in a specified organism against the pathways (or subsystems) in the SEED database, a popular pathway database for bacteria. SEAS maps a given set of genes of a bacterium to pathway genes covered by SEED through gene ID and/or orthology mapping, and then calculates the statistical significance of the enrichment of each relevant SEED pathway by the mapped genes. Our evaluation of SEAS indicates that the program provides highly reliable pathway mapping results and identifies more organism-specific pathways than similar existing programs. SEAS is publicly released under the GPL license agreement and freely available at http://csbl.bmb.uga.edu/~xizeng/research/seas/

Beyond climate envelopes: effects of weather on regional population trends in butterflies

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors