Dengue is an emerging disease in Nepal and was first observed as an outbreak in nine lowland districts in 2006. In 2010, however, a large epidemic of dengue occurred with 4,529 suspected and 917 serologically-confirmed cases and five deaths reported in government hospitals in Nepal. The collection of demographic information was performed along with an entomological survey and clinical evaluation of the patients. A total of 280 serum samples were collected from suspected dengue patients. These samples were subjected to routine laboratory investigations and IgM-capture ELISA for dengue serological identification, and 160 acute serum samples were used for virus isolation, RT-PCR, sequencing and phylogenetic analysis. The results showed that affected patients were predominately adults, and that 10% of the cases were classified as dengue haemorrhagic fever/ dengue shock syndrome. The genetic characterization of dengue viruses isolated from patients in four major outbreak areas of Nepal suggests that the DENV-1 strain was responsible for the 2010 epidemic. Entomological studies identified Aedes aegypti in all epidemic areas. All viruses belonged to a monophyletic single clade which is phylogenetically close to Indian viruses. The dengue epidemic started in the lowlands and expanded to the highland areas. To our knowledge, this is the first dengue isolation and genetic characterization reported from Nepal.

BACKGROUND AND PURPOSE: Prediction of intracranial aneurysm growth risk can assist physicians in planning of follow-up imaging of conservatively managed unruptured intracranial aneurysms. We therefore aimed to externally validate the ELAPSS (Earlier subarachnoid hemorrhage, aneurysm Location, Age, Population, aneurysm Size and Shape) score for prediction of the risk of unruptured intracranial aneurysm growth. METHODS: From 11 international cohorts of patients ≥18 years with ≥1 unruptured intracranial aneurysm and ≥6 months of radiological follow-up, we collected data on the predictors of the ELAPSS score, and calculated 3- and 5-year absolute growth risks according to the score. Model performance was assessed in terms of calibration (predicted versus observed risk) and discrimination (c-statistic). RESULTS: We included 1,072 patients with a total of 1,452 aneurysms. During 4,268 aneurysm-years of follow-up, 199 (14%) aneurysms enlarged. Calibration was comparable to that of the development cohort with the overall observed risks within the range of the expected risks. The c-statistic was 0.69 (95% confidence interval [CI], 0.64 to 0.73) at 3 years, compared to 0.72 (95% CI, 0.68 to 0.76) in the development cohort. At 5 years, the c-statistic was 0.68 (95% CI, 0.64 to 0.72), compared to 0.72 (95% CI, 0.68 to 0.75) in the development cohort. CONCLUSIONS: The ELAPSS score showed accurate calibration for 3- and 5-year risks of aneurysm growth and modest discrimination in our external validation cohort. This indicates that the score is externally valid and could assist patients and physicians in predicting growth of unruptured intracranial aneurysms and plan follow-up imaging accordingly.
Aneurysm ; Calibration ; Cohort Studies ; Discrimination (Psychology) ; Follow-Up Studies ; Humans ; Intracranial Aneurysm ; Risk Factors ; Subarachnoid Hemorrhage

Variety of accessibility to edible species in different regions has climatic and historical roots. In the present study, we try to systematically analyze 28,064 records of relationships between 11,752 edible species and 228 geographic zones by hierarchical clustering. The 228 geographic regions were classified into 11 super groups named as A to K, which were further divided into 39 clusters (CLs). Of them, at least one member of each of 28 CLs is associated to 20 or more edible species according to present information of KNApSAcK DB (http://kanaya.naist.jp/KNApSAcK_World/top.jsp). We examined those 28 CLs and found that majority of the members of each of the 27 CLs (96%) have specific type of climate. Diversity of accessibility to edible species makes it possible to separate 8 geographic regions on continental landmasses namely Mediterraneum, Baltic Sea, Western Europe, Yucatan Peninsula, South America, Africa and Arabian Peninsula, Southeast Asia, and Arctic Ocean; and three archipelagos namely, Caribbean Islands, Southeast Asian Islands and Pacific Islands. In addition, we also examined clusters based on cultural exchanges by colonization and migration and mass movement of people and material by modern transportation and trades as well as biogeographic factors. The era of big data science or data intensive science make it possible to systematically understand the content in huge data and how to acquire suitable data for specific purposes. Human healthcare should be considered on the basis of culture, climate, accessibility of edible foods and preferences, and based on molecular level information of genome and digestive systems.