Right-sided aorta with complete isolation of the left innominate artery

AbstractA right-sided aorta with an isolated left subclavian and left common carotid artery is a rare arch defect. We are presenting the case of a 56-year-old woman who had initially presented with headache and 3 episodes of right-sided facial and extremity numbness. A presumptive diagnosis of transient ischemic attack prompted imaging studies where a computer tomography angiogram showed aberrant vessels

The Importance of Rapid Consideration of Creutzfeldt- Jakob Disease in the Differential Diagnosis of Progressive Neurodegenerative Disease: A Case Report

Background: Creutzfeldt-Jakob disease (CJD) is a prion disease characterized by misfolded proteins that lead to neurodegeneration and inevitable death. Classic sporadic CJD presents primarily with cognitive symptoms and ataxia without visual impairment at the onset of the illness. Seizure activity is a rare presentation of patients with sporadic CJD. Case: We present a rare case of rapidly progressive encephalopathy in a 57-year-old female who presented to the emergency department with bizarre behavior and vision deterioration. Imaging was unrevealing, and infectious and organic causes were ruled out. Electroencephalogram showed evidence of encephalopathy and non-convulsive status epilepticus. Magnetic resonance imaging conducted later displayed high signal intensity in centrum ovale. The patient’s history, results from diagnostic analyses, and clinical presentation suggested the diagnosis of CJD (sporadic type). Conclusion: Due to the low incidence and varying clinical presentations, it is difficult to include CJD in a differential diagnosis without specific analytic measures. However, for the benefit of the patient and healthcare resources, CJD needs to be quickly considered when rapid neurological decline or non-convulsive status epilepticus is not suggestive of another entit

Routine activities and proactive police activity: a macro-scale analysis of police searches in London and New York City

This paper explored how city-level changes in routine activities were associated with changes in frequencies of police searches using six years of police records from the London Metropolitan Police Service and the New York City Police Department. Routine activities were operationalised through selecting events that potentially impacted on (a) the street population, (b) the frequency of crime or (c) the level of police activity. OLS regression results indicated that routine activity variables (e.g. day of the week, periods of high demand for police service) can explain a large proportion of the variance in search frequency throughout the year. A complex set of results emerged, revealing cross-national dissimilarities and the differential impact of certain activities (e.g. public holidays). Importantly, temporal frequencies in searches are not reducible to associations between searches and recorded street crime, nor changes in on-street population. Based on the routine activity approach, a theoretical police-action model is proposed

An Adaptive Interacting Wang-Landau Algorithm for Automatic Density Exploration

While statisticians are well-accustomed to performing exploratory analysis in the modeling stage of an analysis, the notion of conducting preliminary general-purpose exploratory analysis in the Monte Carlo stage (or more generally, the model-fitting stage) of an analysis is an area which we feel deserves much further attention. Towards this aim, this paper proposes a general-purpose algorithm for automatic density exploration. The proposed exploration algorithm combines and expands upon components from various adaptive Markov chain Monte Carlo methods, with the Wang-Landau algorithm at its heart. Additionally, the algorithm is run on interacting parallel chains -- a feature which both decreases computational cost as well as stabilizes the algorithm, improving its ability to explore the density. Performance is studied in several applications. Through a Bayesian variable selection example, the authors demonstrate the convergence gains obtained with interacting chains. The ability of the algorithm's adaptive proposal to induce mode-jumping is illustrated through a trimodal density and a Bayesian mixture modeling application. Lastly, through a 2D Ising model, the authors demonstrate the ability of the algorithm to overcome the high correlations encountered in spatial models.Comment: 33 pages, 20 figures (the supplementary materials are included as appendices

Promoting self-facilitating feedback processes in coastal ecosystem engineers to increase restoration success:Testing engineering measures

Coastal ecosystem engineers often depend on self‐facilitating feedbacks to ameliorate environmental stress. This makes the restoration of such coastal ecosystem engineers difficult. We question if we can increase transplantation success in highly dynamic coastal areas by engineering measures that promote the development of self‐facilitating feedback processes.Intertidal blue mussels Mytilus edulis are a typical example of ecosystem engineers that are difficult to restore. A lack of self‐facilitating feedbacks at low densities limits establishment success when young mussels are transplanted on dynamic mudflats.In a large field experiment, we investigated the possibility of increasing transplantation success by stimulating the formation of an aggregated spatial configuration in mussels, thereby reducing hydrologically induced dislodgment and the risks of predation. For this, we applied engineering measures in the form of fences that trapped wave dislodged mussels.Mussel loss rates were significantly lower when mussels were placed between both artificial fences, and in high densities (4.2 kg/m2) compared with mussels placed in areas without fences and in low densities (2.1 kg/m2). The fences induced the formation of a banded pattern with high local mussel densities, which locally reduced predation.Synthesis and applications. Our results underline the importance of actively promoting the development of self‐facilitating processes, such as aggregation into patterns, in restoration projects of ecosystem engineers. In particular, the current study shows that engineering measures can help to initiate these kinds of self‐facilitating interactions, especially in highly dynamic areas

Supervised prediction of drug–target interactions using bipartite local models

Motivation: In silico prediction of drug–target interactions from heterogeneous biological data is critical in the search for drugs for known diseases. This problem is currently being attacked from many different points of view, a strong indication of its current importance. Precisely, being able to predict new drug–target interactions with both high precision and accuracy is the holy grail, a fundamental requirement for in silico methods to be useful in a biological setting. This, however, remains extremely challenging due to, amongst other things, the rarity of known drug–target interactions

Parkinson's disease plasma biomarkers: An automated literature analysis followed by experimental validation

Diagnosis of Parkinson's disease (PD) is currently assessed by the clinical evaluation of extrapyramidal signs. The identification of specific biomarkers would be advisable, however most studies stop at the discovery phase, with no biomarkers reaching clinical exploitation. To this purpose, we developed an automated literature analysis procedure to retrieve all the background knowledge available in public databases. The bioinformatic platform allowed us to analyze more than 51,000 scientific papers dealing with PD, containing information on 4121 proteins. Out of these, we could track back 35 PD-related proteins as present in at least two published 2-DE maps of human plasma. Then, 9 different proteins (haptoglobin, transthyretin, apolipoprotein A-1, serum amyloid P component, apolipoprotein E, complement factor H, fibrinogen γ, thrombin, complement C3) split into 32 spots were identified as a potential diagnostic pattern. Eventually, we compared the collected literature data to experimental gels from 90 subjects (45 PD patients, 45 non-neurodegenerative control subjects) to experimentally verify their potential as plasma biomarkers of PD

Additive genetic variation for tolerance to estrogen pollution in natural populations of Alpine whitefish (Coregonus sp., Salmonidae)

The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution

Ecosystem services and disservices provided by small rodents in arable fields: effects of local and landscape management

1. In agriculture, both valuable ecosystem services and unwanted ecosystem disservices can be produced by the same organism group. For example, small rodents can provide biological control through weed seed consumption but may also act as pests, causing crop damage. 2. We studied the hypothesised causal relationships between ecosystem services (removal of weed seeds) and disservices (removal of wheat and crop damage) derived by small rodents (voles and mice) at multiple spatial scales. At the landscape scale, we studied the effects of landscape compositional and configurational heterogeneity along the former inner German border in east and west Germany on the abundance of voles and mice and their related ecosystem services and disservices. At the local scale, we studied how this abundance and ecosystem functions are affected by management intensity (organic vs. conventional winter wheat), associated differences in crop characteristics and edge effects. 3. Linear mixed effects models and path analysis show that voles drive ecosystem disservices, but not ecosystem services, in agricultural fields. Daily wheat seed removal by voles was influenced by increasing wheat height and was almost three times higher than weed seed removal, which was not related to local or landscape-scale effects. 4. Abundance of voles and associated crop damage decreased with lower crop density and higher wheat height, which were associated with organic farming. Abundance of voles and crop damage were highest in conventional fields in west Germany. 5. Synthesis and applications. As the ecosystem disservice of wheat seed consumption by voles and mice must be considered mainly during crop sowing, management before harvest should focus on decreasing the pest potential of voles’ but not mice. Our results suggest that densities of voles and their ecosystem disservices could be reduced by having fields with low crop density and high wheat height, practices associated with organic farming. Surrounding landscapes with low compositional and configurational heterogeneity could further reduce voles’ pest potential, but with probable negative effects on farmland biodiversity

Validation of the present day annual cycle in heavy precipitation over the British Islands simulated by 14 RCMs

The representation of the annual cycle of heavy daily precipitation events across the United Kingdom within 14 regional climate models (RCMs) and the European observation data set (E-OBS) over the 1961-2000 period is investigated. We model extreme precipitation as an inhomogeneous Poisson process with a non-stationary threshold and use a sinusoidal model for the location and scale parameter of the corresponding generalized extreme value distribution and a constant shape parameter. First we fit the statistical model to the UK Met Office 5 km gridded precipitation data set (UKMO). Second the statistical model is fitted to 14 reanalysis driven 25 km resolution RCMs from the ENSEMBLES project and to E-OBS. The resulting characteristics from the RCMs and from E-OBS are compared with those from UKMO. We study the peak time of the annual cycle of the monthly return levels, the relative amplitude of their annual cycle and the relative bias of their absolute values. We show that the performance of the RCMs depends strongly on the region. The RCMs show deficits in modeling the characteristics of the annual cycle, especially in modeling its relative amplitude and mainly in Eastern England. However the peak time of the annual cycle is adequately simulated by most RCMs. E-OBS exhibits considerable biases in the absolute values of all monthly return levels, but the relative amplitude and the phase of the annual cycle of heavy precipitation are well represented. Our results imply that studies which rely on the explicit annual cycle of simulated heavy precipitation should be carefully considered