505 research outputs found
Primary psoas abscess extending to thigh adductors: case report
<p>Abstract</p> <p>Background</p> <p>Psoas abscess is a rare condition consisting of pyomyositis of the psoas. The worldwide incidence was 12 cases per 100,000 per year in 1992, but the current incidence is unknown. Psoas abscess can descend along the psoas sheath and reach the inner upper third of the thigh, but only infrequently does it penetrate the sheath and involve the thigh adductors. Because of insidious clinical presentation, the diagnosis of psoas abscess is a challenge. Delayed diagnosis can result in poor prognosis.</p> <p>Case presentation</p> <p>A 45-year-old male with no significant past medical history presented with pain in the left thigh, and limitation of movement at the left hip and knee joint for one month. Ultrasound, CT, and MRI revealed a liquid mass in the left psoas. Percutaneous drainage of this mass yielded 300 ml pus from the psoas. After surgery, the patient reported relief of pain; however, ten days after removal of the drainage tube, the patient complained of persistent pain in his left thigh. CT revealed that the psoas abscess had extended inferiorly, and involved the entire set of adductors of the left thigh. Open surgical drainage was performed at the flank and at the thigh, yielding 350 ml of pus from the thigh. After open drainage and adequate antibiotic therapy, the patient made a good recovery. Follow-up CT confirmed complete resolution of the abscess.</p> <p>Conclusions</p> <p>Large psoas abscess can penetrate the psoas sheath, and descend to thigh adductors even after percutaneous drainage. Appropriate treatment includes open surgical drainage along with antibiotic therapy.</p
The Schrdinger-Poisson equations as the large-N limit of the Newtonian N-body system: applications to the large scale dark matter dynamics
In this paper it is argued how the dynamics of the classical Newtonian N-body
system can be described in terms of the Schrdinger-Poisson equations
in the large limit. This result is based on the stochastic quantization
introduced by Nelson, and on the Calogero conjecture. According to the Calogero
conjecture, the emerging effective Planck constant is computed in terms of the
parameters of the N-body system as , where is the gravitational constant, and are the
number and the mass of the bodies, and is their average density. The
relevance of this result in the context of large scale structure formation is
discussed. In particular, this finding gives a further argument in support of
the validity of the Schrdinger method as numerical double of the
N-body simulations of dark matter dynamics at large cosmological scales.Comment: Accepted for publication in the Euro. Phys. J.
Accuracy and repeatability of wrist joint angles in boxing using an electromagnetic tracking system
© 2019, The Author(s). The hand-wrist region is reported as the most common injury site in boxing. Boxers are at risk due to the amount of wrist motions when impacting training equipment or their opponents, yet we know relatively little about these motions. This paper describes a new method for quantifying wrist motion in boxing using an electromagnetic tracking system. Surrogate testing procedure utilising a polyamide hand and forearm shape, and in vivo testing procedure utilising 29 elite boxers, were used to assess the accuracy and repeatability of the system. 2D kinematic analysis was used to calculate wrist angles using photogrammetry, whilst the data from the electromagnetic tracking system was processed with visual 3D software. The electromagnetic tracking system agreed with the video-based system (paired t tests) in both the surrogate ( 0.9). In the punch testing, for both repeated jab and hook shots, the electromagnetic tracking system showed good reliability (ICCs > 0.8) and substantial reliability (ICCs > 0.6) for flexion–extension and radial-ulnar deviation angles, respectively. The results indicate that wrist kinematics during punching activities can be measured using an electromagnetic tracking system
A systematic review on health resilience to economic crises
Background The health effects of recent economic crises differ markedly by population group. The objective of this systematic review is to examine evidence from longitudinal studies on factors influencing resilience for any health outcome or health behaviour among the general population living in countries exposed to financial crises. Methods We systematically reviewed studies from six electronic databases (EMBASE, Global Health, MEDLINE, PsycINFO, Scopus, Web of Science) which used quantitative longitudinal study designs and included: (i) exposure to an economic crisis; (ii) changes in health outcomes/behaviours over time; (iii) statistical tests of associations of health risk and/or protective factors with health outcomes/behaviours. The quality of the selected studies was appraised using the Quality Assessment Tool for Quantitative Studies. PRISMA reporting guidelines were followed. Results From 14,584 retrieved records, 22 studies met the eligibility criteria. These studies were conducted across 10 countries in Asia, Europe and North America over the past two decades. Ten socio-demographic factors that increased or protected against health risk were identified: gender, age, education, marital status, household size, employment/occupation, income/ financial constraints, personal beliefs, health status, area of residence, and social relations. These studies addressed physical health, mortality, suicide and suicide attempts, mental health, and health behaviours. Women’s mental health appeared more susceptible to crises than men’s. Lower income levels were associated with greater increases in cardiovascular disease, mortality and worse mental health. Employment status was associated with changes in mental health. Associations with age, marital status, and education were less consistent, although higher education was associated with healthier behaviours. Conclusions Despite widespread rhetoric about the importance of resilience, there was a dearth of studies which operationalised resilience factors. Future conceptual and empirical research is needed to develop the epidemiology of resilience
Integration of decision support systems to improve decision support performance
Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species
Background
The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS.
Results
We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features.
Conclusions
This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA
Educating and Informing Patients Receiving Psychopharmacological Medications: Are Family Physicians in Pakistan up to the Task?
Introduction: Studies have shown a high prevalence of psychiatric illnesses among Patients in primary health care settings. Family physicians have a fundamental role in managing psychiatric illness with psychopharmacological medications. Providing information about the disease, its management and the potential adverse effects of the medications is an important part of the management of mental illnesses. Our objective was to determine if Patients who were prescribed psychopharmacological drugs by family physicians at a community health center in Karachi, Pakistan were provided adequate education about their disease and its management. Methods: A cross-sectional study was conducted at the Community Health Centre (CHC), Aga Khan University Hospital Karachi, Pakistan. Details about the prescriptions and Patient education were acquired from the Patients after their consultations. Results: A total of 354 adult Patients were interviewed during 3 days. Among them, 73 (20.6%) were prescribed psychopharmacological medications. Among Patients receiving psychopharmacological medicines, 37 (50.7%) did not know their diagnosis, 50 (68.5%) were unaware of the disease process, 52 (71.2%) were unaware of alternative treatments, 63 (86.3%) were not cautioned about the potential adverse effects of the drugs, 24 (32.9%) were unaware of the duration of treatment and in 60 (82.2%) of the participants an appropriate referral had not been discussed. For all aspects of education, Patients prescribed psychopharmacological medications knew less as compared to those Patients that were prescribed other medications. Discussion: The practice of imparting information to Patients who receive psychopharmacological medications seems to be inadequate in Pakistan. We have hypothesized about the possible reasons for our findings, and identified a need for further research to determine the cause for such findings and to address them accordingly. At the same time there is a need to educate family physicians in Pakistan about the special importance of providing adequate information to such Patients
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Global solar wind variations over the last four centuries
The most recent “grand minimum” of solar activity, the Maunder minimum (MM, 1650–1710), is of great interest both for understanding the solar dynamo and providing insight into possible future heliospheric conditions. Here, we use nearly 30 years of output from a data-constrained magnetohydrodynamic model of the solar corona to calibrate heliospheric reconstructions based solely on sunspot observations. Using these empirical relations, we produce the first quantitative estimate of global solar wind variations over the last 400 years. Relative to the modern era, the MM shows a factor 2 reduction in near-Earth heliospheric magnetic field strength and solar wind speed, and up to a factor 4 increase in solar wind Mach number. Thus solar wind energy input into the Earth’s magnetosphere was reduced, resulting in a more Jupiter-like system, in agreement with the dearth of auroral reports from the time. The global heliosphere was both smaller and more symmetric under MM conditions, which has implications for the interpretation of cosmogenic radionuclide data and resulting total solar irradiance estimates during grand minima
TRY plant trait database - enhanced coverage and open access
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Chronic Respiratory Aeroallergen Exposure in Mice Induces Epithelial-Mesenchymal Transition in the Large Airways
Chronic allergic asthma is characterized by Th2-polarized inflammation and leads to airway remodeling and fibrosis but the mechanisms involved are not clear. To determine whether epithelial-mesenchymal transition contributes to airway remodeling in asthma, we induced allergic airway inflammation in mice by intranasal administration of house dust mite (HDM) extract for up to 15 consecutive weeks. We report that respiratory exposure to HDM led to significant airway inflammation and thickening of the smooth muscle layer in the wall of the large airways. Transforming growth factor beta-1 (TGF-β1) levels increased in mouse airways while epithelial cells lost expression of E-cadherin and occludin and gained expression of the mesenchymal proteins vimentin, alpha-smooth muscle actin (α-SMA) and pro-collagen I. We also observed increased expression and nuclear translocation of Snail1, a transcriptional repressor of E-cadherin and a potent inducer of EMT, in the airway epithelial cells of HDM-exposed mice. Furthermore, fate-mapping studies revealed migration of airway epithelial cells into the sub-epithelial regions of the airway wall. These results show the contribution of EMT to airway remodeling in chronic asthma-like inflammation and suggest that Th2-polarized airway inflammation can trigger invasion of epithelial cells into the subepithelial regions of the airway wall where they contribute to fibrosis, demonstrating a previously unknown plasticity of the airway epithelium in allergic airway disease
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