A prospective study of monitoring practices for metabolic disease in antipsychotic-treated community psychiatric patients

<p>Abstract</p> <p>Background</p> <p>Patients with severe mental illness are at increased risk for metabolic and cardiovascular disease. A number of recent guidelines and consensus statements recommend stringent monitoring of metabolic function in individuals receiving antipsychotic drugs.</p> <p>Methods</p> <p>We conducted a prospective cohort study of 106 community-treated psychiatric patients from across the diagnostic spectrum from the Northeast of England to investigate changes in metabolic status and monitoring practices for metabolic and cardiovascular disease. We undertook detailed anthropometric and metabolic assessment at baseline and follow-up, and examined clinical notes and hospital laboratory records to ascertain monitoring practices.</p> <p>Results</p> <p>A high prevalence of undiagnosed and untreated metabolic disease was present at baseline assessment. Mean follow-up time was 599.3 (SD ± 235.4) days. Body mass index (p < 0.005) and waist circumference (p < 0.05) had significantly increased at follow-up, as had the number of individuals who were either overweight or obese. Fifty-three per cent of individuals had hypertriglyceridemia, and 31% had hypercholesterolemia, but only 7% were receiving lipid-lowering therapy. Monitoring practices were poor. Recording of measures of adiposity occurred in 0% of individuals, and > 50% of subjects had neither blood glucose nor lipids monitored during the follow-up period.</p> <p>Conclusion</p> <p>This cohort has a high prevalence of metabolic disease and heightened cardiovascular risk. Despite the publication of a number of recommendations regarding physical health screening in this population, monitoring rates are poor, and physical health worsened during the follow-up period.</p

Identification of financial statement fraud in Greece by using computational intelligence techniques

The consequences of financial fraud are an issue with far-reaching for investors, lenders, regulators, corporate sectors and consumers. The range of development of new technologies such as cloud and mobile computing in recent years has compounded the problem. Manual detection which is a traditional method is not only inaccurate, expensive and time-consuming but also they are impractical for the management of big data. Auditors, financial institutions and regulators have tried to automated processes using statistical and computational methods. This paper presents comprehensive research in financial statement fraud detection by using machine learning techniques with a particular focus on computational intelligence (CI) techniques. We have collected a sample of 2469 observations since 2002 to 2015. Research gap was identified as none of the existing researchers address the association between financial statement fraud and CI-based detection algorithms and their performance, as reported in the literature. Also, the innovation of this research is that the selection of data sample is aimed to create models which will be capable of detecting the falsification in financial statements

The Salmonella effector SseJ disrupts microtubule dynamics when ectopically expressed in Normal Rat Kidney cells

Salmonella effector protein SseJ is secreted by Salmonella into the host cell cytoplasm where it can then modify host cell processes. Whilst host cell small GTPase RhoA has previously been shown to activate the acyl-transferase activity of SseJ we show here an un-described effect of SseJ protein production upon microtubule dynamism. SseJ prevents microtubule collapse and this is independent of SseJ's acyl-transferase activity. We speculate that the effects of SseJ on microtubules would be mediated via its known interactions with the small GTPases of the Rho family

Association of herd BRSV and BHV-1 seroprevalence with respiratory disease and reproductive performance in adult dairy cattle

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to detect the associations between bovine herpesvirus 1 (BHV-1) status of a herd and respiratory disease (BRD) occurrence and reproductive performance in pregnant heifers and cows. The association between management-related factors and higher BRD occurrence was also estimated.</p> <p>Methods</p> <p>Serum samples, collected from cows and youngstock from 103 dairy cattle herds, were analyzed for antibodies against BHV-1, bovine respiratory syncytial virus (BRSV), bovine viral diarrhoea virus (BVDV), and <it>Mycoplasma bovis</it>. A questionnaire was used to collect data concerning herd management factors and reproductive performance, as well as the occurrence of clinical signs of respiratory disease in the last two years, as evaluated by the veterinarian or farm manager. Multiple correspondence analysis (MCA) and logistic regression analysis were performed to identify and quantify the risk factors.</p> <p>Results</p> <p>A low to moderate prevalence (1-49%) of BRSV antibodies among youngstock was associated with a high occurrence of respiratory disease (OR = 6.2, p = 0.010) in cows and in-calf heifers. Employees of the farm may participate in the spread of such disease. Larger herd size, loose-housing of cows, housing youngstock separately from cows until pregnancy, and purchasing new animals were factors possibly related to a high occurrence of respiratory disease symptoms in pregnant heifers and cows. The highest risk of abortions (> 1.3%) and increased insemination index (number of inseminations per pregnancy) (> 1.9) occurred in herds with a moderate prevalence of BHV-1 antibodies (1-49%) in cows.</p> <p>Conclusions</p> <p>BHV-1 was not associated with acute respiratory disease in adult dairy cattle, however was significantly related to reproductive performance. BRSV possesses the main role in respiratory disease complex in adult dairy cattle.</p

Monitoring credit risk in the social economy sector by means of a binary goal programming model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11628-012-0173-7Monitoring the credit risk of firms in the social economy sector presents a considerable challenge, since it is difficult to calculate ratings with traditional methods such as logit or discriminant analysis, due to the relatively small number of firms in the sector and the low default rate among cooperatives. This paper intro- duces a goal programming model to overcome such constraints and to successfully manage credit risk using economic and financial information, as well as expert advice. After introducing the model, its application to a set of Spanish cooperative societies is described.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). Monitoring credit risk in the social economy sector by means of a binary goal programming model. 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Measuring efficiency and productivity in professional football teams: Evidence from the English Premier League

Professional football clubs are unusual businesses, their performance judged on and off the field of play. This study is concerned with measuring the efficiency of clubs in the English Premier League. Information from clubs’ financial statements is used as a measure of corporate performance. To measure changes in efficiency and productivity the Malmquist non-parametric technique has been used. This is derived from the Data Envelopment Analysis (DEA) linear programming approach, with Canonical Correlation Analysis (CCA) being used to ensure the cohesion of the input-output variables. The study concludes that while clubs operate close to efficient levels for the assessed models, there is limited technological advance in their performance in terms of the displacement of the technological frontier

Default risk, state ownership and the cross-section of stock returns: evidence from China

We apply a structural model to estimate firm-level default risk in China and investigate the stock return predictability of default risk and the moderating effects of state ownership for the sample period from 2003 to 2015. We show unique evidence that in China, default risk is positively associated with expected stock returns and state ownership matters considerably to the return predictability of default risk. We find investors of state-owned enterprises (SOEs) are not compensated appropriately in China despite of their higher default risk exposure. Our empirical evidence supports the conjecture on shareholder advantages and suggests that a strong bargaining power of equity holders would have a negative impact on stock returns

What are the consequences of combining nuclear and mitochondrial data for phylogenetic analysis? Lessons from Plethodon salamanders and 13 other vertebrate clades

<p>Abstract</p> <p>Background</p> <p>The use of mitochondrial DNA data in phylogenetics is controversial, yet studies that combine mitochondrial and nuclear DNA data (mtDNA and nucDNA) to estimate phylogeny are common, especially in vertebrates. Surprisingly, the consequences of combining these data types are largely unexplored, and many fundamental questions remain unaddressed in the literature. For example, how much do trees from mtDNA and nucDNA differ? How are topological conflicts between these data types typically resolved in the combined-data tree? What determines whether a node will be resolved in favor of mtDNA or nucDNA, and are there any generalities that can be made regarding resolution of mtDNA-nucDNA conflicts in combined-data trees? Here, we address these and related questions using new and published nucDNA and mtDNA data for <it>Plethodon </it>salamanders and published data from 13 other vertebrate clades (including fish, frogs, lizards, birds, turtles, and mammals).</p> <p>Results</p> <p>We find widespread discordance between trees from mtDNA and nucDNA (30-70% of nodes disagree per clade), but this discordance is typically not strongly supported. Despite often having larger numbers of variable characters, mtDNA data do not typically dominate combined-data analyses, and combined-data trees often share more nodes with trees from nucDNA alone. There is no relationship between the proportion of nodes shared between combined-data and mtDNA trees and relative numbers of variable characters or levels of homoplasy in the mtDNA and nucDNA data sets. Congruence between trees from mtDNA and nucDNA is higher on branches that are longer and deeper in the combined-data tree, but whether a conflicting node will be resolved in favor mtDNA or nucDNA is unrelated to branch length. Conflicts that are resolved in favor of nucDNA tend to occur at deeper nodes in the combined-data tree. In contrast to these overall trends, we find that <it>Plethodon </it>have an unusually large number of strongly supported conflicts between data types, which are generally resolved in favor of mtDNA in the combined-data tree (despite the large number of nuclear loci sampled).</p> <p>Conclusions</p> <p>Overall, our results from 14 vertebrate clades show that combined-data analyses are not necessarily dominated by the more variable mtDNA data sets. However, given cases like <it>Plethodon</it>, there is also the need for routine checking of incongruence between mtDNA and nucDNA data and its impacts on combined-data analyses.</p