Health and lifestyle of Nepalese migrants in the UK

Background: The health status and lifestyle of migrants is often poorer than that of the general population of their host countries. The Nepalese represent a relatively small, but growing, immigrant community in the UK, about whom very little is known in term of public health. Therefore, our study examined the health and lifestyle of Nepalese migrants in the UK. Methods: A cross-sectional survey of Nepalese migrants in UK was conducted in early 2007 using a postal, self-administered questionnaire in England and Scotland (n = 312), and telephone interviews in Wales (n = 15). The total response rate was 68% (327 out of 480). Data were analyzed to establish whether there are associations between socio-economic and lifestyle factors. A multivariate binary logistic regression was applied to find out independent effect of personal factors on health status. Results: The majority of respondents was male (75%), aged between 30 and 45 (66%), married or had a civil partner (83%), had university education (47%) and an annual family income (69%) ranging from £5,035 to £33,300. More than one third (39%) of the respondents have lived in the UK for 1 to 5 years and approximately half (46%) were longer-term residents. Most (95%) were registered with a family doctor, but only 38% with a dentist. A low proportion (14%) of respondents smoked but more than half (61%) consumed alcohol. More than half (57%) did not do regular exercises and nearly one fourth (23%) of respondents rated their health as poor. Self reported 'good' health status of the respondents was independently associated with immigration status and doing regular exercise Conclusion: The self reported health status and lifestyle, health seeking behaviour of Nepalese people who are residing in UK appears to be good. However, the overall regular exercise and dentist registration was rather poor. Health promotion, especially aimed at Nepalese migrants could help encourage them to exercise regularly and assist them to register with a dentist

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

Evaluation of Digital Auscultation to Diagnose Pneumonia in Children 2 to 35 Months of Age in a Clinical Setting in Kathmandu, Nepal: A Prospective Case-Control Study

Objective The objective of this study was to determine the diagnostic validity of digital chest auscultation to improve the differentiation of chest sounds associated with pneumonia in children. Methods This is a prospective case-control study at two hospitals in Nepal. Cases had World Health Organization-defined pneumonia and were classified as radiologically confirmed or nonconfirmed based on radiographic findings. Controls had no respiratory complaints. The presence of crepitations in recorded lung sounds defined pneumonia. Radiologically confirmed pneumonia was the reference standard. Results Sensitivity and specificity of digital auscultation were 56% (95% confidence interval [CI], 40-70%) and 73% (95% CI, 70-76%), respectively. Conclusion Digital auscultation in conjunction with standardized grading of digital lung sounds has the potential to improve the specificity of pneumonia diagnosis, but further development of objective interpretation of lung sounds is needed

Deployment Strategies for Reconfigurable Satellite Constellations

With the emerging democratization of space, Earth Observation (EO) imagery is becoming increasingly important to a variety of industries. However, it remains difficult and expensive to build constellations that achieve continuous and high-quality global coverage. Reconfiguring a satellite constellation into different orbital planes to change its observational performance is traditionally a fuel intensive procedure. The concept of a reconfigurable constellation (ReCon) accounts for J2 perturbation effects when making fuel efficient maneuvers to shift a satellite’s ground track. ReCon reduces the cost of high revisit frequency, high-quality resolution, EO constellations compared to nonreconfigurable constellations by reducing the number of satellites required to achieve repeated observations of a given ground event on demand. This paper first explores the sensitivities of ReCon’s performance against uncertainties in reconfiguration demand, design costs, and imagery value. The sensitivity analysis reveals that in cases of extremely low demand, ReCon fails to provide a cost-effective solution in terms of events responded to per dollar spent. In cases of high demand ReCon fails to meet demand altogether. A Monte Carlo analysis over a range of demand scenarios shows using a staged deployment for ReCon offers a flexible, cost-effective solution to the uncertainties in the demand of EO imagery. Deferring launch costs to the future, through a staged deployment, not only provides flexibility in constellation design, but also allows the designer to capitalize on the continuation of lowering launch costs and increasing launch opportunities. Staging the deployment of constellations also allows for the satellites’ technology to evolve over time, facilitating the capture of higher value imagery and further enhancing the capabilities of ReCon. Implementing the option to deploy additional satellites in stages makes ReCon significantly better equipped to respond to the uncertainty in the demand of space assets