Potentially toxic metals in historic landfill sites: Implications for grazing animals

Municipal waste disposal is an increasing global problem, frequently solved by the use of landfill sites. Following closure, such sites contain a legacy of pollutants and must be managed to provide a safe and useful end life. The soils and vegetation from four historic landfill sites were analysed to determine the extent of pollution by potentially toxic metals (PTMs). Data were subsequently assessed to determine if post closure uses involving grazing were safe for the animals. The heaviest and widest spread soil contamination was due to Ni. Concentrations at all sites exceeded the 95th percentile value for rural soils, in one case by a factor of 30. Cu and Pb contamination was identified at some sites, but no evidence of Al or Zn contamination was found. Oral bioaccessibility testing showed that the availability of Ni in soil was exceedingly low, whilst that of Cu and Pb was high. Concentrations in plant shoots differed significantly amongst the sites, but interspecific differences in shoot concentration were only significant in the case of Cu. The results indicated that exposure levels to grazers would be at or below tolerable levels, indicating that it is generally safe to graze historic landfill. However, animals could be exposed to higher levels of PTMs than would be expected from rural locations, and grazing under conditions where soil consumption may be high could result in levels of exposure to Al, Ni and Pb exceeding tolerable levels. © Springer International Publishing 2014

A novel pathway producing dimethylsulphide in bacteria is widespread in soil environments

The volatile compound dimethylsulphide (DMS) is important in climate regulation, the sulphur cycle and signalling to higher organisms. Microbial catabolism of the marine osmolyte dimethylsulphoniopropionate (DMSP) is thought to be the major biological process generating DMS. Here we report the discovery and characterisation of the first gene for DMSP-independent DMS production in any bacterium. This gene, mddA, encodes a methyltransferase that methylates methanethiol (MeSH) and generates DMS. MddA functions in many taxonomically diverse bacteria including sediment-dwelling pseudomonads, nitrogen-fixing bradyrhizobia and cyanobacteria, and mycobacteria, including the pathogen Mycobacterium tuberculosis. The mddA gene is present in metagenomes from varied environments, being particularly abundant in soil environments, where it is predicted to occur in up to 76% of bacteria. This novel pathway may significantly contribute to global DMS emissions, especially in terrestrial environments, and could represent a shift from the notion that DMSP is the only significant precursor of DMS

Challenges of Profile Likelihood Evaluation in Multi-Dimensional SUSY Scans

Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist confidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MultiNest, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MultiNest configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MultiNest is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.Comment: 21 pages, 9 figures, 1 table; minor changes following referee report. Matches version accepted by JHE

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

Peri-orbital foreign body: a case report

<p>Abstract</p> <p>Introduction</p> <p>Foreign bodies inside the orbital cavity are rare. They can cause more or less serious complications, depending on their nature and size.</p> <p>Case presentation</p> <p>We report a case of a work-related accident involving a peri-orbital foreign body. The patient was a 50-year-old Caucasian man whose face was injured on the right side while he was working with an agricultural machine. On admission, he was fully conscious and did not have any neurological deficits. He had no loss of vision or ocular motility, but had a laceration of the lateral side of his right upper eyelid. A computed tomographic scan revealed a 6-cm-long bended metal object lodged in the lateral bulbar space of the right orbit. The patient recovered well after surgery and a course of antibiotic therapy.</p> <p>Conclusion</p> <p>The original aspects of this case are the singularity of the foreign body and its relative harmlessness in spite of its large size.</p

Comparative effectiveness of dipeptidyl peptidase-4 (DPP-4) inhibitors and human glucagon-like peptide-1 (GLP-1) analogue as add-on therapies to sulphonylurea among diabetes patients in the Asia-Pacific region: a systematic review

The prevalence of diabetes mellitus is rising globally, and it induces a substantial public health burden to the healthcare systems. Its optimal control is one of the most significant challenges faced by physicians and policy-makers. Whereas some of the established oral hypoglycaemic drug classes like biguanide, sulphonylureas, thiazolidinediones have been extensively used, the newer agents like dipeptidyl peptidase-4 (DPP-4) inhibitors and the human glucagon-like peptide-1 (GLP-1) analogues have recently emerged as suitable options due to their similar efficacy and favorable side effect profiles. These agents are widely recognized alternatives to the traditional oral hypoglycaemic agents or insulin, especially in conditions where they are contraindicated or unacceptable to patients. Many studies which evaluated their clinical effects, either alone or as add-on agents, were conducted in Western countries. There exist few reviews on their effectiveness in the Asia-Pacific region. The purpose of this systematic review is to address the comparative effectiveness of these new classes of medications as add-on therapies to sulphonylurea drugs among diabetic patients in the Asia-Pacific countries. We conducted a thorough literature search of the MEDLINE and EMBASE from the inception of these databases to August 2013, supplemented by an additional manual search using reference lists from research studies, meta-analyses and review articles as retrieved by the electronic databases. A total of nine randomized controlled trials were identified and described in this article. It was found that DPP-4 inhibitors and GLP-1 analogues were in general effective as add-on therapies to existing sulphonylurea therapies, achieving HbA1c reductions by a magnitude of 0.59–0.90% and 0.77–1.62%, respectively. Few adverse events including hypoglycaemic attacks were reported. Therefore, these two new drug classes represent novel therapies with great potential to be major therapeutic options. Future larger-scale research should be conducted among other Asia-Pacific region to evaluate their efficacy in other ethnic groups

Beyond 'Criminology vs. Zemiology': Reconciling crime with social harm

Since its emergence at the start of the twenty-first century, zemiology and the field of harm studies more generally, has borne an ambiguous and, at times, seemingly antipathetic relationship with the better-established field of criminology. Whilst the tension between the perspectives is, at times, overstated, attempts to reconcile the perspectives have also proved problematic, such that, at present, it appears that they risk either becoming polarized into mutually antagonistic projects, or harmonized to the point that zemiology is simply co-opted within criminology. Whilst tempting to view this as nothing more than an academic squabble, it is the central argument put forward in this chapter that the current trend towards either polariziaton or harmonization of the criminological and zemiological projects, risks impoverishing both perspectives, both intellectually and, more fundamentally, in terms of their capacity to effect meaningful social change. To this end, this chapter offers a critical reflection of recent attempts to reconcile the social harm perspective with criminology, focussing in particular on Majid Yar’s attempts to do so using the concept of ‘recognition’ derived from critical theory. It is suggested that such attempts, whilst important in the contribution they make to developing a theory of harm, are necessarily flawed by their reliance on an implicit assumption of a shared conception of harm underpinning both the concept of ‘crime’ and ‘social harm’. By contrast, it is the central argument put forward in this chapter that zemiology and criminology are best understood as divergent normative projects which, whilst sharing many of the same goals with regards to the improvement of the criminal justice system and the tackling of social problems, differ primarily in the means by which they seek to achieve these. Therefore, rather than denying this debate through the collapsing of one perspective into the other, or polarizing them into hostiles camps, it is only by recognising the nature of this debate and fostering dialogue between the perspectives that we can achieve our shared goals and effect meaningful change

A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request

Time series modeling for syndromic surveillance

BACKGROUND: Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. METHODS: Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. RESULTS: Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. CONCLUSIONS: Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization

High prevalence of vitamin D insufficiency and its association with obesity and metabolic syndrome among Malay adults in Kuala Lumpur, Malaysia

Background: Vitamin D status, as indicated by 25-hydroxyvitamin D is inversely associated with adiposity, glucose homeostasis, lipid profiles, and blood pressure along with its classic role in calcium homeostasis and bone metabolism. It is also shown to be inversely associated with metabolic syndrome and cardiovascular diseases in western populations. However, evidence from the Asian population is limited. Therefore, we aim to study the prevalence of vitamin D insufficiency (< 50 nmol/L) and the association of 25-hydroxyvitamin D with metabolic risk factors among an existing Malay cohort in Kuala Lumpur. Methods: This is an analytical cross sectional study. A total of 380 subjects were sampled and their vitamins D status (25-hydroxyvitamin D), fasting blood glucose, full lipid profile were assessed using venous blood. Systolic and diastolic blood pressure, weight, height and waist circumference were measured following standard protocols. Socio-demographic data such as sex, age, smoking status etc were also collected. Data was analysed using t-test, chi-square test, General Linear Model and multiple logistic regression. Results: Females made up 58 of the sample. The mean age of respondents was 48.5 (SD 5.2) years. Females had significantly lower mean Vitamin D levels (36.2; 95 CI: 34.5, 38.0 nmol/L) compared to males (56.2; 95 CI: 53.2, 59.2 nmol/L). Approximately 41 and 87 of males and females respectively had insufficient (< 50 nmol/L) levels of 25-hydroxyvitamin D (p < 0.001). The prevalence of Metabolic Syndrome for the whole sample was 38.4 (95 CI: 33.5, 43.3). In the multivariate model (adjusted for age, sex, abdominal obesity, HDL-cholesterol, diastolic blood pressure), insufficient Vitamin D status was significantly associated with 1-year age increments (OR: 0.93; 95 CI: 0.88, 0.98), being female (OR: 8.68; 95 CI: 5.08, 14.83) and abdominal obesity (OR: 2.57; 95 CI: 1.51, 4.39). Respondents with insufficient vitamin D were found to have higher odds of having Metabolic Syndrome (OR: 1.73; 95 CI: 1.02, 2.92) after adjusting for age and sex. Conclusions: Our results highlight the high prevalence of vitamin D insufficiency among Malay adults in Kuala Lumpur. Vitamin D insufficiency is independently associated with younger age, female sex and greater abdominal obesity. Vitamin D insufficiency is also associated with Metabolic Syndrome