Our result suggests that the risk of lung cancer is affected by smoking, alcohol drinking, and the genetic polymorphism of NQO1. In particular, genetic polymorphisms for NQO1, CYP2E1, and ALDH2 synergistically with cumulative smoking amounts and alcohol drinking levels interact in the carcinogenesis of lung cancer in Koreans.

Environmental dietary carcinogens and genetic polymorphisms in metabolic enzymes have been reported to be the risk factors for gastric cancer. This study was undertaken to investigate the effects of the diet, the N-acetyltransferase (NAT) 2 acetylation status and their interaction on gastric cancer risk. The study population consisted of 471 gastric cancer patients and 471 age-and sexmatched control subjects. NAT2 genotypes were identified using single-nucleotide primer extension reaction methods. Thirty-one alleles related to 12 polymorphism sites were assayed in this study. Significantly increased odds ratios were observed in former smokers (OR 5 2.39, 95% CI 5 1.57-3.62), heavy drinkers (OR 5 1.28, 95% CI 5 1.06-1.55) and individuals who eat well-done meat (OR 5 1.24, 95% CI 5 1.09-1.41). The odds ratios (95% CI) for high intake of kimchi, stews and soybean paste were 3.27 (2.44-4.37), 1.96 (1.50-2.58) and 1.63 (1.24-2.14), respectively. The NAT2 genotype alone was not associated with gastric cancer risk. A significant gene-environment interaction was observed between environmental carcinogens and NAT2 genotypes. The odds ratios for kimchi, stews and soybean paste were higher in slow/intermediate acetylators than in rapid acetylators. The odds ratios for slow/intermediate acetylators were 2.28 (95% CI: 1.29-4.04) for light smokers and 3.42 (95% CI: 2.06-5.68) for well-done meat intake. The NAT2 acetylator genotype may be an important modifier of the effects of environmental factors on gastric cancer risk. ' 2009 UICC

Objective. The present study investigated whether optic nerve sheath diameter (ONSD) could be used to predict neurological outcomes in post-cardiac arrest (CA) patients. Methods. We performed a comprehensive literature search in the Cochrane Library, ScienceDirect, PubMed, and Web of Science from inception to June 2020 for eligible articles. Stata 14.0 software was used to calculate the pooled odds ratios (ORs) and 95% confidence intervals (95% CIs), sensitivity, specificity, summary receiver operating characteristic (SROC) curve, subgroup analysis, sensitivity analysis, and publication bias. Results. Eight studies involving 473 patients were considered eligible for this meta-analysis. The pooled result using a random-effects model showed that broadened ONSD is associated with poor neurological outcomes in post-CA patients ( OR = 15.62 , 95% CI: 5.50–44.34, P < 0.001 ; I 2 = 58.4 %, P = 0.018 ), with a sensibility of 0.60 (95% CI: 0.45–0.73) and specificity of 0.94 (95% CI: 0.83–0.98). The area under the curve of the SROC curve for ONSD was 0.87 (95% CI: 0.84–0.90). Subgroup analysis revealed that sample size and time of ONSD measurement may be the source of heterogeneity. Sensitivity analysis demonstrated the stability of the results of this meta-analysis. No publication bias using Deeks’ funnel plot was noted across the studies ( P = 0.23 ). Conclusion. This meta-analysis confirmed that ONSD can be used to predict neurological outcomes in post-CA patients.

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Acetaldehyde production during ethanol metabolism has been implicated as an important link between oxidative stress and cell damage, which suggests that oxidative stress caused by ethanol exposure may be more severe in aldehyde dehydrogenase 2 (ALDH2)-deficient individuals than in those with wild-type ALDH2. We evaluated the activities of the major antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), in liver tissue isolated from Aldh2 +/+ and Aldh2 -/-mice that were exposed to ethanol. The activities of CAT and GPx were significantly increased by ethanol treatment in Aldh2 +/+ mice (3.33-fold and 1.65-fold, respectively). The mean activity of SOD in Aldh2 +/+ mice was 1.46-fold that in the Aldh2 +/+ control group, but the difference was not statistically significant. In Aldh2 -/-mice, the activities of SOD and CAT were decreased and that of GPx was slightly increased after ethanol exposure, but the differences were not significant. We postulate that antioxidant enzyme expression after ethanol consumption may differ according to the intracellular level of acetaldehyde or free radicals, which in turn depends on the activity of ALDH2. These results suggest that the greater toxicity of ethanol in Aldh2 -/-mice than in Aldh2 +/+ mice may be due to decreased antioxidant enzyme expression.

Urinary hippuric acid (HA) has been widely used as a biological marker of occupational exposure to toluene, although it is no longer valid for low levels of toluene exposure. Toluene exposure is known to induce oxidative DNA damage and the metabolism is affected by genetic polymorphisms of some metabolizing enzymes. Therefore, genetic polymorphisms of these metabolizing enzymes must be considered in the evaluation of oxidative stress caused by toluene exposure. We evaluated the relationship between urinary 8-hydroxydeoxyguanosine (8-OHdG), a marker of oxidative DNA damage, and urinary HA in individuals without occupational exposure to toluene and characterized the possible roles of GSTM1, GSTT1, and aldehyde dehydrogenase 2 (ALDH2) genotypes in the relationships between these markers. In this study, we enrolled 92 healthy Koreans. Urinary HA and 8-OHdG levels were measured and the correlations between them were statistically tested according to the GSTM1, GSTT1, and ALDH2 genotypes. HA did not significantly correlate with urinary 8-OHdG in overall subjects. However, the correlation between them showed a statistical significance in individuals with GSTM1-null, GSTT1-null, and ALDH2 *2/*2 genotypes (r = 0.766, p < 0.01). This study shows that the relationship between urinary HA and 8-OHdG concentration is modified by genetic polymorphisms of some metabolizing enzymes such as GSTM1, GSTT1, and ALDH2.

No abstract

. During the software developing, more and more software designments are failed because of the requirements change. Requirements change has becoming the main error source of software developing, and it directly influences the quality of software. In this paper, we analyze the types of requirements change and its influence on the software developing. Our analysis will provide references for implement of the requirements change in software developing.