Transmission of West Nile Virus by Culex quinquefasciatus Say Infected with Culex Flavivirus Izabal

Unlike most known flaviviruses (Family, Flaviviridae: Genus, Flavivirus), insect-only flaviviruses are a unique group of flaviviruses that only infect invertebrates. The study of insect-only flaviviruses has increased in recent years due to the discovery and characterization of numerous novel flaviviruses from a diversity of mosquito species around the world. The widespread discovery of these viruses has prompted questions regarding flavivirus evolution and the potential impact of these viruses on the transmission of flaviviruses of public health importance such as WNV. Therefore, we tested the effect of Culex flavivirus Izabal (CxFV Izabal), an insect-only flavivirus isolated from Culex quinquefasciatus mosquitoes in Guatemala, on the growth and transmission of a strain of WNV isolated concurrently from the same mosquito species and location. Prior infection of C6/36 (Aedes albopictus mosquito) cells or Cx. quinquefasciatus with CxFV Izabal did not alter the replication kinetics of WNV, nor did it significantly affect WNV infection, dissemination, or transmission rates in two different colonies of mosquitoes that were fed blood meals containing varying concentrations of WNV. These data demonstrate that CxFV probably does not have a significant effect on WNV transmission efficiency in nature

Big Data and Causality

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Causality analysis continues to remain one of the fundamental research questions and the ultimate objective for a tremendous amount of scientific studies. In line with the rapid progress of science and technology, the age of big data has significantly influenced the causality analysis on various disciplines especially for the last decade due to the fact that the complexity and difficulty on identifying causality among big data has dramatically increased. Data mining, the process of uncovering hidden information from big data is now an important tool for causality analysis, and has been extensively exploited by scholars around the world. The primary aim of this paper is to provide a concise review of the causality analysis in big data. To this end the paper reviews recent significant applications of data mining techniques in causality analysis covering a substantial quantity of research to date, presented in chronological order with an overview table of data mining applications in causality analysis domain as a reference directory