Polymorphism of the DNA repair gene XPA and susceptibility to lung cancer

Objective： To study the relationship between one polymorphism in the promoter of the DNA repair gene XPA and the susceptibility to lung cancer. Methods： Genotypes were determined by the PCR-restriction fragment length polymorphism （PCR-RFLP） method in 310 histologically-confirmed lung cancer cases and 341 age and sex frequency-matched cancer-free controls. Results： The XPA A23G genotype frequencies were 27.1% （AA）, 42.9% （AG）, and 30.0% （GG） in case patients and21.1% （AA）, 5218% （AG）, and 26.1% （C-G） in control subjects. Multivariate logistic regression analysis revealed that individuals carrying at least one 23G variant allele （AG ＋ GG genotypes） had a significantly decreased risk for lung cancer （adjusted OR = 0.66; 95 % CI = 0.44- 0.98） compared with the wild-type genotype （23AA）. Stratified analysis showed that the protective effect was more evident in subjects with a family history of cancer. Conclusion： These results suggest that the XPA A23G polymorphism may have a role in lung cancer susceptibility in this study population.

Cross-efficiency DEA model-based evaluation of allocative efficiency of rural information resources in Jiangsu Province, China

Purpose: This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province, China as the research sample.Design/methodology/approach: We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings: Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations: We have to give up using some indicators because of limited data availability. There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications: The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value: Little or no research has been published about the allocative efficiency of rural information resources. The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.