The presence of depression and anxiety do not distinguish between functional jerks and cortical myoclonus

INTRODUCTION: Functional movement disorders are accompanied by a high occurrence of psychopathology and cause serious impairments in quality of life. However, little is known about this in patients with functional jerks and no comparison has been made between patients with functional jerks and organic myoclonus. This case control study compares the occurrence of depression, anxiety and quality of life (HR-QoL) in patients with functional jerks and cortical myoclonus. METHODS: Patients with functional jerks and cortical myoclonus, consecutively recruited, were compared on self-rated anxiety (Beck Anxiety Inventory), depression (Beck Depression Inventory), health-related quality of life (RAND-36), and myoclonus severity (UMRS and CGI-S rating scales). RESULTS: Sixteen patients with functional jerks and 23 with cortical myoclonus were evaluated. There was no significant difference in depression (44% vs. 43%) or anxiety (44% vs. 47%) scores between groups. The HR-QoL was similarly impaired except that functional jerks patients reported significantly more pain (p < 0.05). Only in the functional jerks group myoclonus severity correlated with depression and anxiety. CONCLUSION: Depression and anxiety scores are high and do not discriminate between functional jerks and cortical myoclonus. Quality of life was equally impaired in both sub-groups, but pain was significantly worse in patients with functional jerks

The climate change risk management matrix for the grazing industry of northern Australia

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes

Performance of a C4F8O Gas Radiator Ring Imaging Cherenkov Detector Using Multi-anode Photomultiplier Tubes

We report on test results of a novel ring imaging Cherenkov (RICH) detection system consisting of a 3 meter long gaseous C4F8O radiator, a focusing mirror, and a photon detector array based on Hamamatsu multi-anode photomultiplier tubes. This system was developed to identify charged particles in the momentum range from 3-70 GeV/c for the BTeV experiment.Comment: 28 pages, 23 figures, submitted to Nuclear Instruments and Method

Comorbidities, exposure to medications, and the risk of community-acquired clostridium difficile infection: A systematic review and meta-analysis

Background. Clostridium difficile infection (CDI) has been extensively escribedin healthcare settings; however, risk factor sassociated with community-acquired (CA) CDI remain uncertain. This study aimed to synthesize the current evidence for an association between commonly prescribed medications and comorbidities with CA-CDI. methods. A systematic search was conducted in 5 electronic databases for epidemiologicstudi esthatexamined the associtation between the presence of comorbidities and exposure to medications with the risk of CA-CDI. Pooled odds ratios were estimated using 3 meta-analytic methods. Subgroup analyses by location of studies and by life stages were conducted. results. Twelve publications (n=56,776 patients) met inclusion criteria. Antimicrobial (odds ratio, 6.18; 95% CI, 3.80-10.04) and corticosteroid (1.81; 1.15-2.84) exposure were associated with increased risk of CA-CDI. Among the comorbidities, inflammatory bowel disease (odds ratio, 3.72; 95% CI, 1.52-9.12), renal failure (2.64; 1.23-5.68), hematologic cancer (1.75; 1.02-5.68), and diabetes mellitus (1.15; 1.05-1.27) were associated with CA-CDI. By location, antimicrobial exposure was associated with a higher risk of CA-CDI in the United States, whereas proton-pump inhibitor exposure was associated with a higher risk in Europe. By life stages, the risk of CA-CDI associated with antimicrobial exposure greatly increased in adults older than 65 years. conclusions. Antimicrobial exposure was the strongest risk factor associated with CA-CDI. Further studies are required to investigate the risk of CA-CDI associated with medications commonly prescribed in the community. Patients with diarrhea who have inflammatory bowel disease, renal failure, hematologic cancer, or diabetes are appropriate populations for interventional studies of screening

Mycobacterium bovis shedding patterns from experimentally infected calves and the effect of concurrent infection with bovine viral diarrhoea virus

Concurrent infection of cattle with bovine viral diarrhoea virus (BVDV) and Mycobacterium bovis is considered to be a possible risk factor for onward transmission of bovine tuberculosis (BTB) in infected cattle and is known to compromise diagnostic tests. A comparison is made here of M. bovis shedding (i.e. release) characteristics from 12 calves, six experimentally co-infected with BVDV and six infected with M. bovis alone, using simple models of bacterial replication. These statistical and mathematical models account for the intermittent or episodic nature of shedding, the dynamics of within-host bacterial proliferation and the sampling distribution from a given shedding episode. We show that while there are distinct differences among the shedding patterns of calves given the same infecting dose, there is no statistically significant difference between the two groups of calves. Such differences as there are, can be explained solely in terms of the shedding frequency, but with all calves potentially excreting the same amount of bacteria in a given shedding episode post-infection. The model can be thought of as a process of the bacteria becoming established in a number of discrete foci of colonization, rather than as a more generalized infection of the respiratory tract. In this case, the variability in the shedding patterns of the infected calves can be explained solely by differences in the number of foci established and shedding being from individual foci over time. Should maximum exposure on a particular occasion be a critical consideration for cattle-to-cattle transmission of BTB, cattle that shed only intermittently may still make an important contribution to the spread and persistence of the disease

The CLEO-III Ring Imaging Cherenkov Detector

The CLEO-III Detector upgrade for charged particle identification is discussed. The RICH design uses solid LiF crystal radiators coupled with multi-wire chamber photon detectors, using TEA as the photosensor, and low-noise Viking readout electronics. Results from our beam test at Fermilab are presented.Comment: Invited talk by R.J. Mountain at ``The 3rd International Workshop on Ring Imaging Cherenkov Detectors," a research workshop of the Israel Science Foundation, Ein-Gedi, Dead-Sea, Israel, Nov. 15-20, 1998, 14 pages, 9 figure

Water Demand for Generating Electricity - A Mathematical Programming Approach with Application in Poland

This report documents a water demand study developed as a collaborative effort between the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria; the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland; and the Industry Studies Program of the University of Houston, Houston, Texas, USA. The study developed and applied a mathematical programming model of resource in an electric power plant. The model specifically represents a hypothetical, coal-fired plant located on the Vistula River in Poland. The modeling techniques, however, have very general applicability. The report emphasizes issues of water demand in the modeled plant and also discusses coal transportation, and combustion. Major design and operating options for the plant are described, including the cooling system, water treatment processes, choices of coal type, and mode of transport, railroad or slurry pipeline. These options are constrained by identified standards for air and water quality, and the model is constructed to minimize costs of generating specified loads of electricity in accordance with these constraints. The report provides a detailed description of the model's structure, relating each component to the identified options and constraints. Some general issues in modeling industrial operations are discussed. The report concludes with a presentation of illustrative water demand analyses performed with the model. The results are not definitive but highlight the power of the method and the importance of an integrated approach to studying water demand and other aspects of industrial resource use