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Wang, Jingping

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Wang

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Jingping

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Wang, Jingping
Author's Publications: search.filters.isAuthorOfPublication.aed963b9-bf01-4d7a-89a3-1ac034828d42

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    Lack of associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol dependence: review and meta-analysis of retrospective controlled studies
    (BioMed Central, 2017) Kong, Xiangyi; Deng, Hao; Gong, Shun; Alston, Theodore; Kong, Yanguo; Wang, Jingping
    Background: Studies have sought associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol-dependence, but findings are inconsistent. We summarize the information as to associations of rs1799971 (A > G) and the alcohol-dependence. Methods: Systematically, we reviewed related literatures using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Embase, PubMed, Web of Knowledge, and Chinese National Knowledge Infrastructure (CNKI) databases were searched using select medical subject heading (MeSH) terms to identify all researches focusing on the present topic up to September 2016. Odds ratios (ORs) along with the 95% confidence interval (95% CI) were estimated in allele model, homozygote model, heterozygote model, dominant model and recessive model. Ethnicity-specific subgroup-analysis, sensitivity analysis, heterogeneity description, and publication-bias assessment were also analyzed. Results: There were 17 studies, including 9613 patients in the present meta-analysis. The ORs in the 5 genetic-models were 1.037 (95% CI: 0.890, 1.210; p = 0.64), 1.074 (95% CI: 0.831, 1.387; p = 0.586), 1.155 (95% CI: 0.935, 1.427; p = 0.181), 1.261 (95% CI: 1.008, 1.578; p = 0.042), 0.968 (95% CI: 0.758, 1.236; p = 0.793), respectively. An association is significant in the dominant model, but there is no statistical significance upon ethnicity-specific subgroup analysis. Conclusion: The rs1799971 (A > G) is not strongly associated with alcohol-dependence. However, there are study heterogeneities and limited sample sizes.
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    A Simplified Method for Analysis of Polyunsaturated Fatty Acids
    (BioMed Central, 2005) Kang, Jing; Wang, Jingping
    Background: Analysis of fatty acid composition of biological materials is a common task in lipid research. Conventionally, preparation of samples for fatty acid analysis by gas chromatography involves two separate procedures: lipid extraction and methylation. This conventional method is complicated, tedious and time consuming. Development of a rapid and simple method for lipid analysis is warranted. Results: We simplified the conventional method by combining the extraction and methylation into a single step (omitting the procedure of prior extraction). Various biological samples including cultured cells, animal tissues and human specimens have been tested using the new method. Statistical analysis indicates that the recovery of long chain fatty acids from tissue samples by the simplified method is significantly higher than that by the traditional method, but there is no difference in relative fatty acid composition between the two methods. This simplified method can significantly save time and materials, and reduce the potentials of sample loss and contamination. Conclusion: The lipid extraction procedure prior to methylation employed conventionally in lipid analysis can be omitted without affecting the recovery of long chain (≥ 18 C) fatty acids and their composition. The simplified method is rapid, easy-to-use, suitable for analysis of total long chain polyunsaturated fatty acid contents (e.g. n-6 and n-3 fatty acids) in various biological samples, especially when the number of samples to be analyzed is large and/or the specimen size is small.
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    Association of opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with nicotine dependence
    (Impact Journals LLC, 2017) Kong, Xiangyi; Deng, Hao; Alston, Theodore; Kong, Yanguo; Wang, Jingping
    Background and Object Whether opioid-receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) is associated with nicotine dependence is controversial. We analyzed the combined results from published studies of this possibility. Methods: Literature reviews were performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Web of Science, Chinese National Science Infrastructure (CNKI), PubMed, Embase and Google Scholar database searches using MeSH terms were conducted to find all relevant researches up to October 2016. Odds ratios (ORs) and their 95% confidence intervals (95% CIs) were calculated in allele, homozygote, heterozygote, dominant and recessive models. Ethnicity-specific subgroup meta-analysis, heterogeneity, sensitivity analysis and publication bias were considered. Results: Seven eligible studies with 3313 patients were included. The ORs in the five genetic models mentioned above were 1.000 (95% CI: 0.906, 1.104; p = 0.999), 1.032 (95% CI: 0.771, 1.381; p = 0.834), 0.963 (95% CI: 0.799, 1.162; p = 0.696), 1.006 (95% CI: 0.916, 1.104; p = 0.907), 0.967 (95% CI: 0.715, 1.309; p = 0.830), respectively. Only in dominant model is the association significant. Upon ethnicity-specific subgroup analysis, there is no statistical significance. Conclusion: OPRM1-A118G polymorphism (A>G) is not associated with nicotine dependence.