Dataset Information

Genotype and genetic variation of HCV infections with low-risk factors in Putian coastal regions, China.

ABSTRACT: Hepatitis C virus (HCV) infection is one of the leading causes of death and morbidity associated with liver disease. Risk factors identified for the transmission of HCV include contaminated blood products, intravenous drug use, body piercing, an infected mother at birth, sexual activity, and dental therapy, among others. However, the exact diversity of the HCV genotype and genetic variation among patients with low-risk factors is still unknown. In this study, we briefly described and analysed the genotype distribution and genetic variation of HCV infections with low-risk factors using molecular biology techniques. The results suggested that genotype 1b was predominant, followed by genotypes 2a and 1a. Genetic variations in the 5' UTR sequences of HCV were identified, including point mutations, deletions, and insertions. The frequency of genetic variations in 1b was higher than in 2a. This study provides considerable value for the prevention and treatment of liver disease caused by HCV among patients with low-risk factors and for the development of HCV diagnostic reagents and vaccines.

SUBMITTER: Li XM

PROVIDER: S-EPMC9148788 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genotype and genetic variation of HCV infections with low-risk factors in Putian coastal regions, China.

Li X M XM Qiu R X RX Song C H CH Huang Q H QH Wang X D XD Hu Z T ZT He X Z XZ Ye X Y XY Huang X G XG Zheng F F FF Lin G X GX

Epidemiology and infection 20171030 16

Hepatitis C virus (HCV) infection is one of the leading causes of death and morbidity associated with liver disease. Risk factors identified for the transmission of HCV include contaminated blood products, intravenous drug use, body piercing, an infected mother at birth, sexual activity, and dental therapy, among others. However, the exact diversity of the HCV genotype and genetic variation among patients with low-risk factors is still unknown. In this study, we briefly described and analysed th ...[more]

PMID: 29081304

Similar Datasets

Project description:Variations in marine and terrestrial geographical environments can cause considerable differences in meteorological conditions, economic features, and population density (PD) levels between coastal and inland cities, which in turn can affect the urban air quality. In this study, a five-year (2016-2020) dataset encompassing air monitoring (from the China National Environmental Monitoring Centre), socioeconomic statistical (from the Shandong Province Bureau of Statistics) and meteorological data (from the U.S. National Centers for Environmental Information, National Oceanic and Atmospheric Administration) was employed to investigate the spatiotemporal distribution characteristics and underlying drivers of urban ozone (O3) in Shandong Province, a region with both land and sea environments in eastern China. The main research methods included the multiscale geographically weighted regression (MGWR) model and wavelet analysis. From 2016 to 2019, the O3 concentration increased year by year in most cities, but in 2020, the O3 concentration in all cities decreased. O3 concentration exhibited obvious regional differences, with higher levels in inland areas and lower levels in eastern coastal areas. The MGWR analysis results indicated the relationship between PD, urbanization rate (UR), and O3 was greater in coastal cities than that in the inland cities. Furthermore, the wavelet coherence (WTC) analysis results indicated that the daily maximum temperature was the most important factor influencing the O3 concentration. Compared with NO, NO2, and NOx (NOx ≡ NO + NO2), the ratio of NO2/NO was more coherent with O3. In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM2.5) exerted a greater impact on O3 in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O3 differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O3 pollution control in coastal and inland cities.

Dataset Information

Genotype and genetic variation of HCV infections with low-risk factors in Putian coastal regions, China.

Publications

Genotype and genetic variation of HCV infections with low-risk factors in Putian coastal regions, China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets