Insomnia is a common prevalent sleep disorder. Difficulty maintaining sleep or poor in quality in insomnia caused by disrupted or misaligned circadian rhythms may play an important role in the development of atherosclerosis. This study aimed to examine the association between insomnia and subclinical atherosclerosis in Chinese steelworkers.A total of 3240 subjects from a large enterprise located in northern China were included in this study. The Athens Insomnia Scale (AIS) was used to assess the status of insomnia. Subclinical atherosclerosis was evaluated using ultrasonographic measurements of carotid plaque. Multivariable logistic regression was used to identify association between insomnia and carotid atherosclerosis.The overall prevalence of insomnia and carotid plaque were 35.3 and 31.7% in the study population. Compared with non-insomnia workers, significantly increased odds of carotid plaque were observed among insomnia workers after adjusting for potential confounders, odds ratio (OR) = 1.38, 95% confidence interval (CI): 1.17 to 1.63. Exposure to current shift work and insomnia simultaneously can significantly elevated the odds of carotid plaque.Insomnia is associated with elevated odds of carotid atherosclerosis in male steelworkers. Insomnia problems of workers should receive further attention in occupational worker health interventions.
Abstract Background: The characteristics of elephant grass, especially its stem lignocellulose, are of great significance for its quality as feed or other industrial raw materials. However, the research on lignocellulose biosynthesis pathway and key genes is limited because the genome of elephant grass has not been deciphered. Results: In this study, RNA sequencing (RNA-seq) combined with lignocellulose content analysis and cell wall morphology observation using elephant grass stems from different development stages as materials were applied to reveal the genes that regulate the synthesis of cellulose and lignin. A total of 3852 differentially expressed genes (DEGs) were identified in three periods of T1, T2, and T3 through RNA-seq analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of all DEGs showed that the two most abundant metabolic pathways were phenylpropane metabolism, starch and sucrose metabolism, which were closely related to cell wall development, hemicellulose, lignin and cellulose synthesis. Through weighted gene co-expression network analysis (WGCNA) of DEGs, a ‘blue’ module highly associated with cellulose synthesis and a ‘turquoise’ module highly correlated with lignin synthesis were exhibited. A total of 43 candidate genes were screened, of which 17 had function annotations in other species. Besides, by analyzing the content of lignocellulose in the stem tissues of elephant grass at different developmental stages and the expression levels of genes such as CesA , PAL , CAD , C4H , COMT , CCoAMT , F5H and CCR , it was found that the content of lignocellulose was related to the expression level of these structural genes. Conclusions: This study provides a basis for further understanding the molecular mechanisms of cellulose and lignin synthesis pathways of elephant grass, and offers a unique and extensive list of candidate genes for future specialized functional studies which may promote the development of high-quality elephant grass varieties with high cellulose and low lignin content.
Abstract Background: The characteristics of elephant grass, especially its stem lignocellulose, are of great significance for its quality as feed or other industrial raw materials. However, the research on lignocellulose biosynthesis pathway and key genes is limited because the genome of elephant grass has not been deciphered. Results: In this study, RNA sequencing (RNA-seq) combined with lignocellulose content analysis and cell wall morphology observation using elephant grass stems from different development stages as materials were applied to reveal the genes that regulate the synthesis of cellulose and lignin. A total of 3852 differentially expressed genes (DEGs) were identified in three periods of T1, T2, and T3 through RNA-seq analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of all DEGs showed that the two most abundant metabolic pathways were phenylpropane metabolism, starch and sucrose metabolism, which were closely related to cell wall development, hemicellulose, lignin and cellulose synthesis. Through weighted gene co-expression network analysis (WGCNA) of DEGs, a ‘blue’ module highly associated with cellulose synthesis and a ‘turquoise’ module highly correlated with lignin synthesis were exhibited. A total of 43 candidate genes were screened, of which 17 had function annotations in other species. Besides, by analyzing the content of lignocellulose in the stem tissues of elephant grass at different developmental stages and the expression levels of genes such as CesA , PAL , CAD , C4H , COMT , CCoAMT , F5H and CCR , it was found that the content of lignocellulose was related to the expression level of these structural genes. Conclusions: This study provides a basis for further understanding the molecular mechanisms of cellulose and lignin synthesis pathways of elephant grass, and offers a unique and extensive list of candidate genes for future specialized functional studies which may promote the development of high-quality elephant grass varieties with high cellulose and low lignin content.
Occupational exposure to heat stress and noise at the workplace are widespread physical hazards and have been associated with an increase in both morbidity and mortality. This study aims to examine the association between occupational heat stress and noise exposure and carotid atherosclerosis in Chinese steelworkers. A total of 3471 subjects were included in this study. Carotid plaque was measured using ultrasonography. The occupational information was collected by face-to-face personal interviews and all of the reported information was verified with the company's records. Workers were divided into non-exposure and exposure groups according to the company's records regarding previous and/or current heat stress and noise exposure status in the workplace. The prevalence of carotid plaque was 30.1% in the study population and workers exposed to both occupational heat stress and noise had the highest prevalence of carotid plaque at 37.2%. The odds of carotid plaque in individuals of different exposure status were significantly elevated after adjustment for potential confounders, especially in the heat stress and noise exposure combination group: OR = 1.32, 95% CI: 1.06 to 1.65, in individuals who had experienced heat stress exposure; OR = 1.49, 95% CI: 1.18 to 1.88, in individuals who had experienced noise exposure; OR = 2.02, 95% CI: 1.60 to 2.56, in the combination group. No significant association in female workers and no significant multiplicative or additive interactions were found between occupational heat stress and noise exposure and carotid plaque. Exposure to occupational heat stress and noise are statistically associated with carotid atherosclerosis among male steelworkers.
Background It is a daunting task to discontinue pertussis completely in China owing to its growing increase in the incidence. While basic to any formulation of prevention and control measures is early response for future epidemic trends. Discrete wavelet transform(DWT) has been emerged as a powerful tool in decomposing time series into different constituents, which facilitates better improvement in prediction accuracy. Thus we aim to integrate modeling approaches as a decision-making supportive tool for formulating health resources. Methods We constructed a novel hybrid method based on the pertussis morbidity cases from January 2004 to May 2018 in China, where the approximations and details decomposed by DWT were forecasted by a seasonal autoregressive integrated moving average (SARIMA) and nonlinear autoregressive network (NAR), respectively. Then, the obtained values were aggregated as the final results predicted by the combined model. Finally, the performance was compared with the SARIMA, NAR and traditional SARIMA-NAR techniques. Results The hybrid technique at level 2 of db2 wavelet including a SARIMA(0,1,3)(1,0,0)12modelfor the approximation-forecasting and NAR model with 12 hidden units and 4 delays for the detail d1-forecasting, along with another NAR model with 11 hidden units and 5 delays for the detail d2-forecasting notably outperformed other wavelets, SARIMA, NAR and traditional SARIMA-NAR techniques in terms of the mean square error, root mean square error, mean absolute error and mean absolute percentage error. Descriptive statistics exhibited that a substantial rise was observed in the notifications from 2013 to 2018, and there was an apparent seasonality with summer peak. Moreover, the trend was projected to continue upwards in the near future. Conclusions This hybrid approach has an outstanding ability to improve the prediction accuracy relative to the others, which can be of great help in the prevention of pertussis. Besides, under current trend of pertussis morbidity, it is required to urgently address strategically within the proper policy adopted.
The purpose of this study was to determine whether neck circumference (NC) is associated with subclinical atherosclerosis among Chinese steelworkers in North China. A cross-sectional survey was conducted among steelworkers in northern China (n = 3467). Carotid intima-media thickness (CIMT) was measured at the distal wall of the common carotid artery proximal to the bifurcation point along a plaque-free segment 10 mm long on each side by B-ultrasound. The mean of the common CIMT was used bilaterally in this study. In the cross-sectional analysis, large NC was associated with the presence of abnormal CIMT. Logistic regression analysis was used to assess the relationship between NC tertiles and CIMT. The multivariable-adjusted odds ratio was 1.76 (95% CI: 1.40 to 2.22; p for trend <0.001) for the highest tertile versus the lowest tertile and was 1.07 (95% CI: 1.04 to 1.10; p < 0.001) per 1 standard deviation increment in NC. Among steelworkers in North China, relatively large NC level is associated with elevated odds of subclinical atherosclerosis.
Abstract Background: The characteristics of elephant grass, especially its stem lignocellulose, are of great significance for its quality as feed or other industrial raw materials. Because the genome of elephant grass has not been deciphered, the study of its lignocellulose synthesis pathway and key genes is limited. Results: In this study, RNA sequencing (RNA-seq) combining with lignocellulose content analysis and cell wall morphology observation using elephant grass stems from different development stages as materials, were applied to reveal the genes regulating cellulose and lignin synthesis. A total of 3852 differentially expressed genes (DEGs) were identified in three periods of T1, T2 and T3. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the two most abundant metabolic pathways were phenylpropanemetabolism, starch and sucrose metabolism, which closely related to cell wall development, hemicellulose, lignin and cellulose synthesis. Through weighted gene co-expression network analysis (WGCNA) of DEGs, a ‘blue’ module highly correlated with cellulose synthesis and a ‘turquoise’ module highly correlated with lignin synthesis were exhibited. A total of 43 candidate genes were screened, of which 17 had function annotations in other species. In addition, the expression of CesA , PAL , CAD , C4H , COMT , CCoAMT , F5H , CAD and CCR at different development stages were analyzed, and found that the content of lignocellulose was correlated with the expression levels of these structural genes. Conclusions: This study not only provides new insights into the molecular mechanisms of cellulose and lignin synthesis pathways in elephant grass, but also offers a new and extensive list of candidate genes for more specialized functional studies in the future which may promote the development of high-quality elephant grass varieties with high cellulose and low lignin content.
Abstract Non-alcoholic fatty liver disease (NAFLD) is replacing hepatitis B as the leading cause of chronic liver disease in China. The purpose of this study is to select good tools to identify NAFLD from the body composition, anthropometry and related routine clinical parameters. A total of 5076 steelworkers, aged 22–60 years, was included in this study. Body fat mass was measured via bioelectrical impedance analysis (BIA) and fat mass index (FMI) was derived. Ultrasonography method was used to detect hepatic steatosis. Random forest classifier and best subset regression were used to select useful parameters or models that can accurately identify NAFLD. Receiver operating characteristic (ROC) curves were used to describe and compare the performance of different diagnostic indicators and algorithms including fatty liver index (FLI) and hepatic steatosis index (HSI) in NAFLD screening. ROC analysis indicated that FMI can be used with high accuracy to identify heavy steatosis as determined by ultrasonography in male workers [area under the curve (AUC) 0.95, 95% CI 0.93–0.98, sensitivity 89.0%, specificity 91.4%]. The ability of single FMI to identify NAFLD is no less than that of combination panels, even better than the combination panel of HSI. The best subset regression model that including FMI, waist circumference, and serum levels of triglyceride and alanine aminotransferase has moderate accuracy in diagnosing overall NAFLD (AUC 0.83). FMI and the NAFLD best subset (BIC) score seem to be good tools to identify NAFLD in Chinese steelworkers.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)