Oral Blue Nevus of the Lingual Gingiva: A Case Report.

Oral melanocytic nevi (OMN) are rare benign tumors originating from melanocytes with an unclear pathogenesis. The current theory suggests that OMN originate from dormant dendritic melanocytes that become enclosed in the dermis during the embryonic migration of melanoblasts - the precursors of melanocytes - from the neural crest to the epidermis. OMN can be congenital or acquired, with acquired nevi being more common.

Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia.

We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model.

Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX.

We examined the potential added risk posed by global climate change on the dengue vector Aedes aegypti abundance using CLIMEX, a powerful tool for exploring the relationship between the fundamental and realised niche of any species. After calibrating the model using data from several knowledge domains, including geographical distribution records, we estimated potential distributions of the mosquito under current and future potential scenarios. The impact of climate change on its potential distribution was assessed with two global climate models, the CSIRO-Mk3.

Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment.

An important option in preventing the spread of dengue fever (DF) is to control and monitor its vector (Aedes aegypti) as well as to locate and destroy suitable mosquito breeding environments. The aim of the present study was to use a combination of environmental and socioeconomic variables to model areas at risk of DF. These variables include clinically confirmed DF cases, mosquito counts, population density in inhabited areas, total populations per district, water access, neighbourhood quality and the spatio-temporal risk of DF based on the average, weekly frequency of DF incidence.

The importance of appropriate temporal and spatial scales for dengue fever control and management.

It is important to have appropriate models for the surveillance and control of mosquito-borne diseases, such as dengue fever (DF). These models need to be based on appropriate temporal and spatial scales. The aim of this study was to illustrate the impact of different temporal and spatial scales on DF control decisions.

Modeling spatio-temporal risk changes in the incidence of Dengue fever in Saudi Arabia: a geographical information system case study.

The aim of this study was to use geographical information systems to demonstrate the Dengue fever (DF) risk on a monthly basis in Jeddah, Saudi Arabia with the purpose to provide documentation serving to improve surveillance and monitor the Aedes aegypti mosquito vector. Getis-Ord Gi* statistics and a frequency index covering a five-year period (2006-2010) were used to map DF and model the risk spatio-temporally. The results show that monthly hotspots were mainly concentrated in central Jeddah districts and that the pattern changes considerably with time.

Modeling dengue fever risk based on socioeconomic parameters, nationality and age groups: GIS and remote sensing based case study.

Dengue fever (DF) and its impacts are growing environmental, economic, and health concerns in Saudi Arabia. In this study, we have attempted to model areas with humans at risk of dengue fever prevalence, depending on the spatial relationship between dengue fever cases and different socioeconomic parameters. We have developed new methods to verify the quality of neighborhoods from high resolution satellite images based on several factors such as density of houses in each neighborhood in each district, width of streets, and roof area of houses.