Tongue and tail necrosis in an atypical case of acute steroid responsive meningitis-arteritis in a dog

Acute steroid responsive meningitis-arteritis (SRMA) is a common neurological disorder in young dogs. Typical clinical symptoms of the acute form of SRMA are neck pain, depression and fever. This case report describes a 1.5-year-old Pointer with uncommon neurological deficits (unilateral multiple cranial nerve deficits and Homer's syndrome) and an exceptional necrosis of the tongue. This was believed to be part of the systemic vasculitis accompanying SRMA. The patient also developed tail necrosis and iatrogenic calcinosis cutis, which complicated further treatment of the dog

Stenomaps: Shorthand for shapes

We address some of the challenges in representing spatial data with a novel form of geometric abstraction-the stenomap. The stenomap comprises a series of smoothly curving linear glyphs that each represent both the boundary and the area of a polygon. We present an efficient algorithm to automatically generate these open, C1-continuous splines from a set of input polygons. Feature points of the input polygons are detected using the medial axis to maintain important shape properties. We use dynamic programming to compute a planar non-intersecting spline representing each polygon's base shape. The results are stylised glyphs whose appearance may be parameterised and that offer new possibilities in the 'cartographic design space'. We compare our glyphs with existing forms of geometric schematisation and discuss their relative merits and shortcomings. We describe several use cases including the depiction of uncertain model data in the form of hurricane track forecasting; minimal ink thematic mapping; and the depiction of continuous statistical data

Proton radiography to improve proton radiotherapy: Simulation study at different proton beam energies

To improve the quality of cancer treatment with protons, a translation of X-ray Computed Tomography (CT) images into a map of the proton stopping powers needs to be more accurate. Proton stopping powers determined from CT images have systematic uncertainties in the calculated proton range in a patient of typically 3-4\% and even up to 10\% in region containing bone~\cite{USchneider1995,USchneider1996,WSchneider2000,GCirrone2007,HPaganetti2012,TPlautz2014,GLandry2013,JSchuemann2014}. As a consequence, part of a tumor may receive no dose, or a very high dose can be delivered in healthy ti\-ssues and organs at risks~(e.g. brain stem)~\cite{ACKnopf2013}. A transmission radiograph of high-energy protons measuring proton stopping powers directly will allow to reduce these uncertainties, and thus improve the quality of treatment. The best way to obtain a sufficiently accurate radiograph is by tracking individual protons traversing the phantom (patient)~\cite{GCirrone2007,TPlautz2014,VSipala2013}. In our simulations we have used an ideal position sensitive detectors measuring a single proton before and after a phantom, while the residual energy of a proton was detected by a BaF$_{2}$ crystal. To obtain transmission radiographs, diffe\-rent phantom materials have been irradiated with a 3x3~cm$^{2}$ scattered proton beam, with various beam energies. The simulations were done using the Geant4 simulation package~\cite{SAgostinelli2003}. In this study we focus on the simulations of the energy loss radiographs for various proton beam energies that are clinically available in proton radiotherapy.Comment: 6 pages, 6 figures, Presented at Jagiellonian Symposium on Fundamental and Applied Subatomic Physics, 7-12 June, 2015, Krak\'ow, Polan

A reservoir of 'historical' antibiotic resistance genes in remote pristine Antarctic soils

Background: Soil bacteria naturally produce antibiotics as a competitive mechanism, with a concomitant evolution, and exchange by horizontal gene transfer, of a range of antibiotic resistance mechanisms. Surveys of bacterial resistance elements in edaphic systems have originated primarily from human-impacted environments, with relatively little information from remote and pristine environments, where the resistome may comprise the ancestral gene diversity. Methods: We used shotgun metagenomics to assess antibiotic resistance gene (ARG) distribution in 17 pristine and remote Antarctic surface soils within the undisturbed Mackay Glacier region. We also interrogated the phylogenetic placement of ARGs compared to environmental ARG sequences and tested for the presence of horizontal gene transfer elements flanking ARGs. Results: In total, 177 naturally occurring ARGs were identified, most of which encoded single or multi-drug efflux pumps. Resistance mechanisms for the inactivation of aminoglycosides, chloramphenicol and beta-lactam antibiotics were also common. Gram-negative bacteria harboured most ARGs (71%), with fewer genes from Gram-positive Actinobacteria and Bacilli (Firmicutes) (9%), reflecting the taxonomic composition of the soils. Strikingly, the abundance of ARGs per sample had a strong, negative correlation with species richness (r=-0.49, P < 0.05). This result, coupled with a lack of mobile genetic elements flanking ARGs, suggests that these genes are ancient acquisitions of horizontal transfer events. Conclusions: ARGs in these remote and uncontaminated soils most likely represent functional efficient historical genes that have since been vertically inherited over generations. The historical ARGs in these pristine environments carry a strong phylogenetic signal and form a monophyletic group relative to ARGs from other similar environments

Exploring curved schematization

Hand-drawn schematized maps traditionally make extensive use of curves. However, there are few automated approaches for curved schematization most previous work focuses on straight lines. We present a new algorithm for area-preserving curved schematization of geographic outlines. Our algorithm converts a simple polygon into a schematic crossing-free representation using circular arcs. We use two basic operations to iteratively replace consecutive arcs until the desired complexity is reached. Our results are not restricted to arcs ending at input vertices. The method can be steered towards different degrees of 'curviness': we can encourage or discourage the use of arcs with a large central angle via a single parameter. Our method creates visually pleasing results even for very low output complexities. We conducted an online user study investigating the effectiveness of the curved schematizations compared to straight-line schematizations of equivalent complexity. While the visual complexity of the curved shapes was judged higher than those using straight lines, users generally preferred curved schematizations. We observed that curves significantly improved the ability of users to match schematized shapes of moderate complexity to their unschematized equivalents

A laparoscopic approach for removal of ovarian remnant tissue in 32 dogs

Background: Surgical treatment of ovarian remnant syndrome (ORS) in dogs usually necessitates large celiotomies and considerable manipulation of organs because of the relatively deep position of ovarian remnant tissue, large patient size, and often encountered adhesions. In women, laparoscopic treatment of ORS is successful and has significant advantages over laparotomy. Since laparoscopic ovariectomy has significant advantages over open ovariectomy in dogs, including reduced surgical stress and postoperative pain and shorter convalescence period, the rationale for a laparoscopic approach of canine ORS is evident. Feasibility and efficacy of a laparoscopic approach for treatment of ORS in dogs was prospectively evaluated using a standardized protocol for diagnosis, treatment, and follow-up. Treatment success was evaluated by histology of removed tissues, postoperative hormone testing, and long-term clinical follow-up. Results: Thirty-two client-owned predominantly medium and large breed dogs diagnosed with ORS underwent abdominal ultrasound for ovarian remnant localization prior to laparoscopic surgery for removal of ovarian remnants. Tissue dissection and excision was performed using a vessel sealing forceps. Laparoscopy subjectively enabled detailed visibility and facilitated detection and removal of suspected ovarian tissue in all cases. Histology confirmed ovarian origin of removed tissue in all dogs. Additionally, a GnRH stimulation test was performed in fourteen dogs after a median follow-up of 10.5 months, which verified absence of residual functional ovarian remnant tissue in all dogs. Median surgery duration was 97.5 min and mean total convalescence duration, subjectively scored by owners, was 1.5 +/- 0.7 days. No major complications occurred. Adhesions were observed in 79% of the dogs, complicated the surgical approach, and significantly affected surgery duration (85 versus 109 min; p = 0.03). Minor hemorrhage occurred in 12% and significantly increased surgery duration (95.5 versus 128 min; p = 0.02). Trendelenburg position and lateral tilting of the patient were essential for proper access to ovarian remnants. GnRH stimulation test results and/or absence of clinical signs indicative of ORS after a median follow-up period of 22.5 months confirmed treatment efficacy in all dogs. Conclusion: Laparoscopic surgery for ORS in dogs is effective with minimal complications and short convalescence and can successfully replace the conventional, more invasive open surgical procedure

An Algorithmic Framework for Labeling Network Maps

Drawing network maps automatically comprises two challenging steps, namely laying out the map and placing non-overlapping labels. In this paper we tackle the problem of labeling an already existing network map considering the application of metro maps. We present a flexible and versatile labeling model. Despite its simplicity, we prove that it is NP-complete to label a single line of the network. For a restricted variant of that model, we then introduce an efficient algorithm that optimally labels a single line with respect to a given weighting function. Based on that algorithm, we present a general and sophisticated workflow for multiple metro lines, which is experimentally evaluated on real-world metro maps.Comment: Full version of COCOON 2015 pape

Multi-Granular Trend Detection for Time-Series Analysis

Time series (such as stock prices) and ensembles (such as model runs for weather forecasts) are two important types of one-dimensional time-varying data. Such data is readily available in large quantities but visual analysis of the raw data quickly becomes infeasible, even for moderately sized data sets. Trend detection is an effective way to simplify time-varying data and to summarize salient information for visual display and interactive analysis. We propose a geometric model for trend-detection in one-dimensional time-varying data, inspired by topological grouping structures for moving objects in two- or higher-dimensional space. Our model gives provable guarantees on the trends detected and uses three natural parameters: granularity, support-size, and duration. These parameters can be changed on-demand. Our system also supports a variety of selection brushes and a time-sweep to facilitate refined searches and interactive visualization of (sub-)trends. We explore different visual styles and interactions through which trends, their persistence, and evolution can be explored