Zoonotic origin and transmission of Middle East respiratory syndrome coronavirus in the UAE.

Since the emergence of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, there have been a number of clusters of human-to-human transmission. These cases of human-to-human transmission involve close contact and have occurred primarily in healthcare settings, and they are suspected to result from repeated zoonotic introductions. In this study, we sequenced whole MERS-CoV genomes directly from respiratory samples collected from 23 confirmed MERS cases in the United Arab Emirates (UAE). These samples included cases from three nosocomial and three household clusters. The sequences were analysed for changes and relatedness with regard to the collected epidemiological data and other available MERS-CoV genomic data. Sequence analysis supports the epidemiological data within the clusters, and further, suggests that these clusters emerged independently. To understand how and when these clusters emerged, respiratory samples were taken from dromedary camels, a known host of MERS-CoV, in the same geographic regions as the human clusters. Middle East respiratory syndrome coronavirus genomes from six virus-positive animals were sequenced, and these genomes were nearly identical to those found in human patients from corresponding regions. These data demonstrate a genetic link for each of these clusters to a camel and support the hypothesis that human MERS-CoV diversity results from multiple zoonotic introductions.

The present and future disease burden of hepatitis C virus infections with today's treatment paradigm - volume 3.

The total number, morbidity and mortality attributed to viraemic hepatitis C virus (HCV) infections change over time making it difficult to compare reported estimates from different years. Models were developed for 15 countries to quantify and characterize the viraemic population and forecast the changes in the infected population and the corresponding disease burden from 2014 to 2030. With the exception of Iceland, Iran, Latvia and Pakistan, the total number of viraemic HCV infections is expected to decline from 2014 to 2030, but the associated morbidity and mortality are expected to increase in all countries except for Japan and South Korea. In the latter two countries, mortality due to an ageing population will drive down prevalence, morbidity and mortality. On the other hand, both countries have already experienced a rapid increase in HCV-related mortality and morbidity. HCV-related morbidity and mortality are projected to increase between 2014 and 2030 in all other countries as result of an ageing HCV-infected population. Thus, although the total number of HCV countries is expected to decline in most countries studied, the associated disease burden is expected to increase. The current treatment paradigm is inadequate if large reductions in HCV-related morbidity and mortality are to be achieved.

Strategies to manage hepatitis C virus infection disease burden - volume 3.

The hepatitis C virus (HCV) epidemic was forecasted through 2030 for 15 countries in Europe, the Middle East and Asia, and the relative impact of two scenarios was considered: increased treatment efficacy while holding the annual number of treated patients constant and increased treatment efficacy and an increased annual number of treated patients. Increasing levels of diagnosis and treatment, in combination with improved treatment efficacy, were critical for achieving substantial reductions in disease burden. A 90% reduction in total HCV infections within 15 years is feasible in most countries studied, but it required a coordinated effort to introduce harm reduction programmes to reduce new infections, screening to identify those already infected and treatment with high cure rate therapies. This suggests that increased capacity for screening and treatment will be critical in many countries. Birth cohort screening is a helpful tool for maximizing resources. Among European countries, the majority of patients were born between 1940 and 1985. A wider range of birth cohorts was seen in the Middle East and Asia (between 1925 and 1995).

Historical epidemiology of hepatitis C virus (HCV) in select countries - volume 3.

Detailed, country-specific epidemiological data are needed to characterize the burden of chronic hepatitis C virus (HCV) infection around the world. With new treatment options available, policy makers and public health officials must reconsider national strategies for infection control. In this study of 15 countries, published and unpublished data on HCV prevalence, viraemia, genotype, age and gender distribution, liver transplants and diagnosis and treatment rates were gathered from the literature and validated by expert consensus in each country. Viraemic prevalence in this study ranged from 0.2% in Iran and Lebanon to 4.2% in Pakistan. The largest viraemic populations were in Pakistan (7 001 000 cases) and Indonesia (3 187 000 cases). Injection drug use (IDU) and a historically unsafe blood supply were major risk factors in most countries. Diagnosis, treatment and liver transplant rates varied widely between countries. However, comparison across countries was difficult as the number of cases changes over time. Access to reliable data on measures such as these is critical for the development of future strategies to manage the disease burden.

Classification of localized muscle fatigue with genetic programming on sEMG during isometric contraction.

Genetic Programming is used to generate a solution that can classify localized muscle fatigue from filtered and rectified surface electromyography (sEMG). The GP has two classification phases, the GP training phase and a GP testing phase. In the training phase, the program evolved with multiple components. One component analyzes statistical features extracted from sEMG to chop the signal into blocks and label them using a fuzzy classifier into three classes: Non-Fatigue, Transition-to-Fatigue and Fatigue. The blocks are then projected onto a two-dimensional Euclidean space via two further (evolved) program components. K-means clustering is then applied to group similar data blocks. Each cluster is then labeled according to its dominant members. The programs that achieve good classification are evolved. In the testing phase, it tests the signal using the evolved components, however without the use of a fuzzy classifier. As the results show the evolved program achieves good classification and it can be used on any unseen isometric sEMG signals to classify fatigue without requiring any further evolution. The GP was able to classify the signal into a meaningful sequence of Non-Fatigue-->Transition-to-Fatigue-->Fatigue. By identifying a Transition-to Fatigue state the GP can give a prediction of an oncoming fatigue. The genetic classifier gave promising results 83.17% correct classification on average of all signals in the test set, especially considering that the GP is classifying muscle fatigue for ten different individuals.

Effect of water and artificial saliva on mechanical properties of some denture-base materials.

Two artificial saliva samples selected on the basis of being chemically and physically similar to natural saliva were used as saturation media so that we could investigate their effects on mechanical properties of four denture-base materials, and the results were compared with the effect of water on the same materials. Diffusion coefficients in the more viscous saliva were different from those in water but, in general, mechanical properties were similarly affected in all liquids, indicating that the aqueous phase of the artificial medium was a major factor influencing the results.