A Single Nucleotide in Stem Loop II of 5′-Untranslated Region Contributes to Virulence of Enterovirus 71 in Mice

BACKGROUND: Enterovirus 71 (EV71) has emerged as a neuroinvasive virus responsible for several large outbreaks in the Asia-Pacific region while virulence determinant remains unexplored. PRINCIPAL FINDINGS: In this report, we investigated increased virulence of unadapted EV71 clinical isolate 237 as compared with isolate 4643 in mice. A fragment 12 nucleotides in length in stem loop (SL) II of 237 5'-untranslated region (UTR) visibly reduced survival time and rate in mice was identified by constructing a series of infectious clones harboring chimeric 5'-UTR. In cells transfected with bicistronic plasmids, and replicon RNAs, the 12-nt fragment of isolate 237 enhanced translational activities and accelerated replication of subgenomic EV71. Finally, single nucleotide change from cytosine to uridine at base 158 in this short fragment of 5'-UTR was proven to reduce viral translation and EV71 virulence in mice. Results collectively indicated a pivotal role of novel virulence determinant C158 on virus translation in vitro and EV71 virulence in vivo. CONCLUSIONS: These results presented the first reported virulence determinant in EV71 5'-UTR and first position discovered from unadapted isolates

GIS in Seismic Evaluation of Essential Facilities

Abstract: This research used PC ARC/INFO, a geographic information system (GIS), to assess the potential seismic vulnerability of essential facilities in Memphis and Shelby County, Tennessee. The GIS is a powerful tool for spatial operations. It offers a link between spatial data in a computerized map form and related nonspatial attribute files. It has the ability to overlay, compare, and analyze several maps in digital form with speed and efficiency. In order to assess the potential vulnerability of essential facilities, evaluation criteria with rational weighting (including soil type, liquefaction potential, slope, foundation, structural conditions, and important elements of bridges such as detour length and average daily traffic) were identified. This research proved that GIS is a reliable and efficient tool for vulnerability assessment of essential facilities in an earthquake‐prone area. The GIS is convenient and productive in data management. It is easy to produce special‐purpose maps at selected scale and tabular analysis reports in desired format. Results of the study are important for future facility maintenance and improvement and earthquake preparedness /response planning. © 1994 Microcomputers in Civil Engineerin

A COMPLEMENTARY TOOL TO WATER QUALITY INDEX: FUZZY CLUSTERING ANALYSIS

ABSTRACT: A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management. Copyright © 1992, Wiley Blackwell. All rights reserve

A COMPLEMENTARY TOOL TO WATER QUALITY INDEX: FUZZY CLUSTERING ANALYSIS

ABSTRACT: A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management. Copyright © 1992, Wiley Blackwell. All rights reserve