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Previously, we have identified single nucleotide polymorphisms (SNPs) rs7958904 and rs4759314 in long non-coding RNA HOX transcript antisense RNA (HOTAIR) were significantly associated with risk of colorectal and gastric cancer, respectively. Here, we aimed to investigate the association between HOTAIR SNPs and cervical cancer (CC) susceptibility. A total of 1209 cases and 1348 controls were enrolled for association study and genotyped with TaqMan allelic discrimination method. The Cancer Genome Atlas (TCGA) database was utilized for in vivo analysis of allele-specific HOTAIR expression. MTT assay was employed for evaluation of allele-specific cell proliferation. The rs7958904 CC genotype was related to an increased risk of cervical cancer compared with the GG/GC genotypes (OR = 1.57, 95% CI = 1.10–2.25). TCGA database showed the CC tissues with rs7958904 CC genotype had higher HOTAIR expression than those with GG genotype (P = 0.046). MTT assay demonstrated a growth-promoting role of rs7958904 C allele on CC cells. Further functional studies on the effect of rs7958904 on biological behavior of CC cells are needed to confirm and extend our findings. In conclusion, HOTAIR rs7958904 might influence CC susceptibility through modulation of CC cell proliferation, and could serve as a diagnostic biomarker.

This study describes electric bike–related injuries from 2004 to 2010, and suggests injury prevention strategies to reduce electric bike–related injuries in China and other countries. Electric bike–related injuries data were obtained from the Bureau of Traffic Management at the Ministry of Public Security. Linear regression was used to identify statistically significant trends in electric bike–related injuries over the period. The results showed electric bike–related nonfatal injury rate had increased almost 4-fold and mortality rate increased 6-fold from 2004 to 2010. Linear regression showed a significant increase of 0.23 per 100 000 population per year (95% confidence interval = 0.18-0.29, P < .001) in the casualty rate from electric bike–related road traffic injuries. China will face new challenges arising from electric bike–related injuries. Programs need to be developed to prevent nonfatal injuries and fatalities caused by electric bike–related crashes in this country.

Recently, several studies have showed that FAS (rs2234767, rs1800682) and FASL (rs763110) functional single nucleotide polymorphisms (SNPs) were associated with the risk of various cancers. However, the association between cervical cancer risk and the three SNPs above remained inconclusive. In this work, we performed a two-stage case-control study on 1155 cervical cancer patients and 1252 matched healthy controls to determine the roles of the mentioned SNPs in cervical cancer susceptibility. We genotyped the FAS rs2234767, rs1800682, and FASL rs763110 polymorphisms using PCR-TaqMan assays. Results revealed that the rs763110 TT genotype significantly increased the risk of cervical cancer compared with the CC/CT genotype (adjusted OR = 1.70, 95% CI = 1.19-2.42). However, we did not observe any association between the cervical cancer risk and the rs2234767 and rs1800682 polymorphisms. The immunohistochemistry assay showed that patients carrying the rs763110 TT genotype presented a lower cancerous FASL expression than that of the CC/CT genotypes. Chromatin immunoprecipitation (ChIP) and Sequential Chromatin immunoprecipitation assays also demonstrated that OCT1 was recruited to the FASL promoter region and regulated the FASL gene transcription by interacting with C/EBPβ. In conclusion, this study provided evidence indicating that the rs763110 variant in the FASL promoter was associated with the risk of cervical cancer by affecting the binding affinity of the C/EBPβ/OCT1 complex to chromatin.

Genetic variants in miRNAs have attracted more and more attention these years because they are capable of altering miRNA function and/or expression, consequently affecting downstream biological pathways and disease risk. The rs767649 polymorphism, locating in the promoter of miR-155, was recently reported to be able to alter transcriptional activity of miR-155 and relate to lung cancer risk. In this study, we aimed to assess the relationship between rs767649 and cervical cancer (CC) risk. We investigated the association of rs767649 with CC risk in a two-stage case-control study with 1157 cases and 1280 controls. Genotyping was determined with TaqMan allelic discrimination method. The results showed that the rs767649 TT genotype was associated with a significantly reduced risk of CC in both test (549 cases and 603 controls), validation (608 cases and 677 controls) and combined sets [adjusted odds ratio (OR) = 0.67, 95% confidence interval (CI) = 0.51–0.87 for the combined set] compared with the AA/AT genotypes. Moreover, the association was more prominent among patients of age > 49 years and postmenopausal status (OR = 0.56, 95% CI = 0.38–0.83, and 0.60, 0.40–0.89, respectively) and patients with clinical stage I and II CC (OR = 0.67, 95% CI = 0.50–0.91, and 0.60, 0.40–0.92, respectively). Further analyses showed that miR-155 was overexpressed in the CC tissues as compared with normal tissues, suggesting an oncogenic role in CC. Luciferase assay indicated that the transition of A to T allele might lead to miR-155 downregulation at the transcriptional level. In conclusion, rs767649 might be a causal variant for CC susceptibility.

Objective: The objective of this study was to identify the prevalence and potential risk factors of farm vehicle–related road traffic crashes among farm vehicle drivers in southern China. Methods: A cross-sectional study was used to interview 1,422 farm vehicle drivers in southern China. Farm vehicle–related road traffic crashes that occurred from December 2013 to November 2014 were investigated. Data on farm vehicle–related road traffic crashes and related factors were collected by face-to-face interviews. Results: The prevalence of farm vehicle–related road traffic crashes among the investigated drivers was 7.2%. Farm vehicle–related road traffic crashes were significantly associated with self-reported vision problem (adjusted odds ratio [AOR] = 6.48, 95% confidence interval [CI], 3.86–10.87), self-reported sleep disorders (AOR = 10.03, 95% CI, 6.28–15.99), self-reported stress (AOR = 20.47, 95% CI, 9.96–42.08), reported history of crashes (AOR = 5.40, 95% CI, 3.47–8.42), reported history of drunk driving (AOR = 5.07, 95% CI, 2.97–8.65), and reported history of fatigued driving (AOR = 5.72, 95% CI, 3.73–8.78). The number of road traffic crashes was highest in the daytime and during harvest season. In over 96% of farm vehicle–related road traffic crashes, drivers were believed to be responsible for the crash. Major crash-causing factors included improper driving, careless driving, violating of traffic signals or signs, and being in the wrong lane. Conclusion: Findings of this study suggest that farm vehicle–related road traffic crashes have become a burgeoning public health problem in China. Programs need to be developed to prevent farm vehicle–related road traffic crashes in this emerging country.

Purpose Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. Methods A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung–Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. Results The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were −483.679, −475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung–Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. Conclusions This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China.