Mixed exposure effect of seminal metals on semen quality, mediation of total antioxidant capacity, and moderation of GSTM1/GSTT1 gene deletion in Chinese reproductive-aged men.

BACKGROUND: The effects of metal exposure on semen quality and the role of oxidative damage in this process remain unclear. METHODS: We recruited 825 Chinese male volunteers, and 12 seminal metals (Mn, Cu, Zn, Se, Ni, Cd, Pb, Co, Ag, Ba, Tl, and Fe), the total antioxidant capacity (TAC), and reduced glutathione were measured. Semen parameters and GSTM1/GSTT1-null genotypes were also detected. Bayesian kernel machine regression (BKMR) was applied to evaluate the effect of the mixed exposure to metals on semen parameters. The mediation of TAC and moderation of GSTM1/GSTT1 deletion were analyzed. RESULTS: Most seminal metal concentrations were correlated with each other. The BKMR models revealed a negative association between the semen volume and metal mixture, with Cd (cPIP = 0.60) and Mn (cPIP = 0.10) as the major contributors. Compared to fixing all scaled metals at their median value (50th percentiles), fixing the scaled metals at their 75th percentiles decreased the TAC by 2.17 units (95%CI: -2.60, -1.75). Mediation analysis indicated that Mn decreased the semen volume, with 27.82% of this association mediated by TAC. Both the BKMR and multi-linear models showed that seminal Ni was negatively correlated with sperm concentration, total sperm count, and progressive motility, which was modified by GSTM1/GSTT1. Furthermore, Ni and the total sperm count showed a negative association in GSTT1 and GSTM1 null males (ß[95%CI]: 0.328 [-0.521, -0.136]) but not in males with GSTT1 and/or GSTM1. Although Fe and the sperm concentration and total sperm count were positively correlated, they showed inverse "U" shapes in univariate analysis. CONCLUSION: Exposure to the 12 metals was negatively associated with semen volume, with Cd and Mn as the major contributors. TAC may mediate this process. GSTT1 and GSTM1 can modify the reduction in the total sperm count caused by seminal Ni exposure.

Identifying the dose response relationship between seminal metal at low levels and semen quality using restricted cubic spline function.

Environmental exposure to metals, including essential and nonessential elements, may be related to semen quality. Our goal was to explore the continuous relationship between seminal metals and sperm parameters. A restricted cubic spline (RCS) was applied to automatic selection criteria to ascertain the optimal smoothing degree. We recruited 841 male volunteers from Henan Province, China. Eighteen seminal metals, namely Al, Cr, Mn, Cu, Zn, Se, As, Ni, Cd, Pb, Co, V, Rb, Ag, Ba, TI, Fe, and Li, and 21 semen parameters were detected. Seminal malondialdehyde (MDA) was also detected to express oxidative stress. We revealed a non-linear relationship of the vanadium and chromium exposure to semen parameters. There were inverse 'U' shapes found between seminal Cr and sperm concentrations, total sperm count, and semen quality. The best semen quality was observed when the seminal Cr concentration was 5.05 ppb, and an increase or decrease in chromium concentration led to decreased semen quality. The V concentration was associated with reduced sperm concentration, total sperm count, normal morphology, and progressive motility at high doses (V > 0.58 ppb). Seminal MDA had a strong adverse association with sperm motility parameters, such as curve line velocity (VCL) (P < 0.001), straight line velocity (VSL) (P = 0.004), velocity of average path (VAP) (P < 0.001), and lateral head movement (ALH) (P = 0.001), whereas it was adversely associated with seminal Zn (ß [95% confidence interval (CI)], -0.28(-0.41-0.16), P < 0.001) after adjusting for confounding factors. Our findings represent the curves of the dose-response relationship between seminal Cr, seminal V, and semen quality, in which seminal MDA was a good indicator of sperm movement. These models provide new insight into the dose-relationship between metal exposure and semen quality, and further investigation is needed to validate this.

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), called the EEMD-ARIMA-NARANN model, to perform time series modeling and forecasting based on the COVID-19 prevalence and mortality data from 28 February 2020 to 27 June 2020 in South Africa and Nigeria. By comparing the accuracy level of forecasting measurements with the basic ARIMA and NARANN models, it was shown that this novel data-driven hybrid model did a better job of capturing the dynamic changing trends of the target data than the others used in this work. Our proposed mixture technique can be deemed as a helpful policy-supportive tool to plan and provide medical supplies effectively. The overall confirmed cases and deaths were estimated to reach around 176,570 [95% uncertainty level (UL) 173,607 to 178,476] and 3454 (95% UL 3384 to 3487), respectively, in South Africa, along with 32,136 (95% UL 31,568 to 32,641) and 788 (95% UL 775 to 804) in Nigeria on 12 July 2020 using this data-driven EEMD-ARIMA-NARANN hybrid technique. The contributions of this study include three aspects. First, the proposed hybrid model can better capture the dynamic dependency characteristics compared with the individual models. Second, this new data-driven hybrid model is constructed in a more reasonable way relative to the traditional mixture model. Third, this proposed model may be generalized to estimate the epidemic patterns of COVID-19 in other regions.

Gene-Environment Interactions Between Environmental Response Genes Polymorphisms and Mitochondrial DNA Copy Numbers Among Benzene Workers.

OBJECTIVE: To determine the effect of mitochondrial DNA copy number (mtDNAcn) as a biomarker of benzene exposure. METHODS: A total of 294 benzene-exposed workers and 102 controls were recruited. Biomarkers of mtDNAcn, cytokinesis-block micronucleus (MN) frequency, and peripheral blood white blood cells (WBC) were detected. Eighteen polymorphism sites in DNA damage repair and metabolic genes were analyzed. RESULTS: Benzene exposure increased mtDNAcn and indicated a dose-response relationship (P < 0.001). mtDNAcn was negatively correlated with WBC count and DNA methylation and positively correlated with MN frequency. The AG type in rs1695 interacted with benzene exposure to aggravate mtDNAcn (ß = 0.006, 95% CI: 0, 0.012, P = 0.050). rs13181, rs1695, rs1800975, and GSTM1 null were associated with benzene-induced mtDNAcn. Rs1695 interacted with benzene to increase mitochondrial damage. CONCLUSIONS: Benzene exposure increases mtDNAcn levels in benzene-exposed workers.

Use of meteorological parameters for forecasting scarlet fever morbidity in Tianjin, Northern China.

The scarlet fever incidence has increased drastically in recent years in China. However, the long-term relationship between climate variation and scarlet fever remains contradictory, and an early detection system is lacking. In this study, we aim to explore the potential long-term effects of variations in monthly climatic parameters on scarlet fever and to develop an early scarlet-fever detection tool. Data comprising monthly scarlet fever cases and monthly average climatic variables from 2004 to 2017 were retrieved from the Notifiable Infectious Disease Surveillance System and National Meteorological Science Center, respectively. We used a negative binomial multivariable regression to assess the long-term impacts of weather parameters on scarlet fever and then built a novel forecasting technique by integrating an autoregressive distributed lag (ARDL) method with a nonlinear autoregressive neural network (NARNN) based on the significant meteorological drivers. Scarlet fever was a seasonal disease that predominantly peaked in spring and winter. The regression results indicated that a 1 °C increment in the monthly average temperature and a 1-h increment in the monthly aggregate sunshine hours were associated with 17.578% (95% CI 7.674 to 28.393%) and 0.529% (95% CI 0.035 to 1.025%) increases in scarlet fever cases, respectively; a 1-hPa increase in the average atmospheric pressure at a 1-month lag was associated with 12.996% (95% CI 9.972 to 15.919%) decrements in scarlet fever cases. Based on the model evaluation criteria, the best-performing basic and combined approaches were ARDL(1,0,0,1) and ARDL(1,0,0,1)-NARNN(5, 22), respectively, and this hybrid approach comprised smaller performance measures in both the training and testing stages than those of the basic model. Climate variability has a significant long-term influence on scarlet fever. The ARDL-NARNN technique with the incorporation of meteorological drivers can be used to forecast the future epidemic trends of scarlet fever. These findings may be of great help for the prevention and control of scarlet fever.

The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004-2018.

Evidence on the long-term influence of climatic variables on pertussis is limited. This study aims to explore the long-term quantitative relationship between weather variability and pertussis. Data on the monthly number of pertussis cases and weather parameters in Chongqing in the period of 2004-2018 were collected. Then, we used a negative binomial multivariable regression model and cointegration testing to examine the association of variations in monthly meteorological parameters and pertussis. Descriptive statistics exhibited that the pertussis incidence rose from 0.251 per 100,000 people in 2004 to 3.661 per 100,000 persons in 2018, and pertussis was a seasonal illness, peaked in spring and summer. The results from the regression model that allowed for the long-term trends, seasonality, autoregression, and delayed effects after correcting for overdispersion showed that a 1 hPa increment in the delayed one-month air pressure contributed to a 3.559% (95% CI 0.746-6.293%) reduction in the monthly number of pertussis cases; a 10 mm increment in the monthly aggregate precipitation, a 1 °C increment in the monthly average temperature, and a 1 m/s increment in the monthly average wind velocity resulted in 3.641% (95% CI 0.960-6.330%), 19.496% (95% CI 2.368-39.490%), and 3.812 (95% CI 1.243-11.690)-fold increases in the monthly number of pertussis cases, respectively. The roles of the mentioned weather parameters in the transmission of pertussis were also evidenced by a sensitivity analysis. The cointegration testing suggested a significant value among variables. Climatic factors, particularly monthly temperature, precipitation, air pressure, and wind velocity, play a role in the transmission of pertussis. This finding will be of great help in understanding the epidemic trends of pertussis in the future, and weather variability should be taken into account in the prevention and control of pertussis.

Dataset on the effect of Benzene exposure on genetic damage, hematotoxicity, telomere length and polymorphisms in metabolic and DNA repair genes.

In this paper, we present an occupational dataset to evaluate benzene exposure on the effective biomarkers of genetic damage, indicated as cytokinesis-block micronucleus (MN) frequency, hematotoxicity, indicated as white blood cells (WBC) counts, and molecular marker of telomere length (TL). And we further to eliminate the mechanism of benzene induced damage. Then evaluate the effects of sites polymorphism in environmental response genes, including 18 sites in metabolic and DNA repair genes, and the interaction between gene polymorphism and benzene exposure. This dataset is supplementary to the submitted research by [1] focused on the biomarkers TL, and a detailed description of the subjects sampling, biomarkers detection, data analysis and discussion are discussed in detail.

Time series analysis of temporal trends in hemorrhagic fever with renal syndrome morbidity rate in China from 2005 to 2019.

Hemorrhagic fever with renal syndrome (HFRS) is seriously endemic in China with 70%~90% of the notified cases worldwide and showing an epidemic tendency of upturn in recent years. Early detection for its future epidemic trends plays a pivotal role in combating this threat. In this scenario, our study investigates the suitability for application in analyzing and forecasting the epidemic tendencies based on the monthly HFRS morbidity data from 2005 through 2019 using the nonlinear model-based self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) methods. The experimental results manifested that the SETAR and LSTAR approaches presented smaller values among the performance measures in both two forecasting subsamples, when compared with the most extensively used seasonal autoregressive integrated moving average (SARIMA) method, and the former slightly outperformed the latter. Descriptive statistics showed an epidemic tendency of downturn with average annual percent change (AAPC) of -5.640% in overall HFRS, however, an upward trend with an AAPC = 1.213% was observed since 2016 and according to the forecasts using the SETAR, it would seemingly experience an outbreak of HFRS in China in December 2019. Remarkably, there were dual-peak patterns in HFRS incidence with a strong one occurring in November until January of the following year, additionally, a weak one in May and June annually. Therefore, the SETAR and LSTAR approaches may be a potential useful tool in analyzing the temporal behaviors of HFRS in China.

Interaction effects of environmental response gene polymorphisms and benzene exposure on telomere length in shoe-making workers.

Benzene is a globally occurring environmental and occupational pollutant that causes leukemia. To better understand telomere length (TL) as a function of benzene toxicity, we recruited 294 shoe-making workers and 102 controls from Wenzhou, China in 2011. Biomarkers of TL, cytokinesis-block micronucleus (MN) frequency, and white blood cells (WBC) were measured. In total, 18 polymorphic sites in environmental response genes, including metabolic and DNA repair genes, were analyzed. Results indicate that benzene exposure led to a longer TL at a threshold of 32 mg/m3-year of cumulative exposure dose (CED). Furthermore, the TL was longer in members of the damaged group, when evaluated for MN frequency (P < 0.001) and reduced WBC (P < 0.001), than in those of the normal group. Workers carrying genotype TT (ß = 0.32, P = 0.042) in rs3212986 of ERCC1 and genotype TC (ß = 0.24, P = 0.082) in rs1051740 of mEH exon3 were associated with a longer TL as compared to the wild-type group. TA (ß = -0.53, P < 0.001) in rs6413432 of CYP2E1 was associated with a shorter TL. Benzene exposure interacted with the TA type in rs6413432 (ß = 0.003, 95% CI: 0, 0.006, P = 0.042) and the CC type in rs1051740 (ß = 0.007, 95% CI: 0.001, 0.013, P = 0.015) after adjusting for confounding factors. Our results indicate that benzene induces an increase in TL at a threshold of CED ≥32mg/m3-year. Rs1051740, rs3212986, and rs6413432 were found to be involved in benzene-induced telomere growth; in particular, rs1051740 and rs6413432 interacted with the benzene exposure, resulting in an extended TL.

Promoter hypermethylation in CSF3R induces peripheral neutrophil reduction in benzene-exposure poisoning.

Benzene is a global pollutant and has been established to cause leukemia. To better understand the role of DNA methylation in benzene toxicity, peripheral blood mononuclear cells were collected from six benzene-poisoning patients and six matched controls for genome-wide DNA methylation screening by Illumina Infinium Methylation 450 BeadChip. The Gene Chip Human Gene 2.0 ST Array (Affymetrix) was used to analyze global mRNA expression. Compared with the corresponding sites of controls, 442 sites in patients were hypermethylated, corresponding to 253 genes, and 237 sites were hypomethylated, corresponding to 130 genes. The promoter methylation and mRNA expression of CSF3R, CREB5, and F2R were selected for verification by bisulfite sequencing and real-time PCR in a larger data set with 21 cases and 23 controls. The results indicated that promoter methylation of CSF3R (p = .005) and F2R (p = .015) was significantly higher in cases than in controls. Correlation analysis showed that the promoter methylation of CSF3R (p < .001) and F2R (p < .001) was highly correlated with its mRNA expression. In the poisoning cases, neutrophil percentage was significantly different among the high, middle, and low CSF3R-methylation groups (p = .002). In particular, the neutrophil percentage in the high CSF3R-methylation group (48.10 ± 9.63%) was significantly lower than that in the low CSF3R-methylation group (59.30 ± 6.26%) (p = .012). The correlation coefficient between promoter methylation in CSF3R and the neutrophil percentage was -0.445 (p = .020) in cases and - 0.398 (p = .060) in controls. These results imply that hypermethylation occurs in the CSF3R promoter due to benzene exposure and is significantly associated with a reduction in neutrophils.

An Advanced Data-Driven Hybrid Model of SARIMA-NNNAR for Tuberculosis Incidence Time Series Forecasting in Qinghai Province, China.

PURPOSE: Qinghai province has invariably been under an ongoing threat of tuberculosis (TB), which has not only been an obstacle to local development but also hampers the prevention and control process for ending the TB epidemic. Forecasting for future epidemics will serve as the base for early detection and planning resource requirements. Here, we aim to develop an advanced detection technique driven by the recent TB incidence series, by fusing a seasonal autoregressive integrated moving average (SARIMA) with a neural network nonlinear autoregression (NNNAR). METHODS: We collected the TB incidence data between January 2004 and December 2016. Subsequently, the subsamples from January 2004 to December 2015 were employed to measure the efficiency of the single SARIMA, NNNAR, and hybrid SARIMA-NNNAR approaches, whereas the hold-out subsamples were used to test their predictive performances. We finally selected the best-performing technique by considering minimum metrics including the mean absolute error, root-mean-squared error, mean absolute percentage error and mean error rate . RESULTS: During 2004-2016, the reported TB cases totaled 71,080 resulting in the morbidity of 97.624 per 100,000 persons annually in Qinghai province and showed notable peak activities in late winter and early spring. Moreover, the TB incidence rate was surging by 5% per year. According to the above-mentioned criteria, the best-fitting basic and hybrid techniques consisted of SARIMA(2,0,2)(1,1,0)12, NNNAR(7,1,4)12 and SARIMA(2,0,2)(1,1,0)12-NNNAR(3,1,7)12, respectively. Amongst them, the hybrid technique showed superiority in both mimic and predictive parts, with the lowest values of the measured metrics in both the parts. The sensitivity analysis indicated the same results. CONCLUSION: The best-mimicking SARIMA-NNNAR hybrid model outperforms the best-simulating basic SARIMA and NNNAR models, and has a potential application in forecasting and assessing the TB epidemic trends in Qinghai. Furthermore, faced with the major challenge of the ongoing upsurge in TB incidence in Qinghai, there is an urgent need for formulating specific preventive and control measures.

Secular Seasonality and Trend Forecasting of Tuberculosis Incidence Rate in China Using the Advanced Error-Trend-Seasonal Framework.

OBJECTIVE: Tuberculosis (TB) is a major public health problem in China, and contriving a long-term forecast is a useful aid for better launching prevention initiatives. Regrettably, such a forecasting method with robust and accurate performance is still lacking. Here, we aim to investigate its potential of the error-trend-seasonal (ETS) framework through a series of comparative experiments to analyze and forecast its secular epidemic seasonality and trends of TB incidence in China. METHODS: We collected the TB incidence data from January 1997 to August 2019, and then partitioning the data into eight different training and testing subsamples. Thereafter, we constructed the ETS and seasonal autoregressive integrated moving average (SARIMA) models based on the training subsamples, and multiple performance indices including the mean absolute deviation, mean absolute percentage error, root-mean-squared error, and mean error rate were adopted to assess their simulation and projection effects. RESULTS: In the light of the above performance measures, the ETS models provided a pronounced improvement for the long-term seasonality and trend forecasting in TB incidence rate over the SARIMA models, be it in various training or testing subsets apart from the 48-step ahead forecasting. The descriptive results to the data revealed that TB incidence showed notable seasonal characteristics with predominant peaks of spring and early summer and began to be plunging at on average 3.722% per year since 2008. However, this rate reduced to 2.613% per year since 2015 and furthermore such a trend would be predicted to continue in years ahead. CONCLUSION: The ETS framework has the ability to conduct long-term forecasting for TB incidence, which may be beneficial for the long-term planning of the TB prevention and control. Additionally, considering the predicted dropping rate of TB morbidity, more particular strategies should be formulated to dramatically accelerate progress towards the goals of the End TB Strategy.

Low-level lead exposure is associated with aberrant sperm quality and reproductive hormone levels in Chinese male individuals: Results from the MARHCS study low-level lead exposure is associated with aberrant sperm quality.

Studies in animals suggest an adverse effect of high-level lead exposure on male reproductive outcomes. However, evidence of the effects of low-level lead exposure is inconsistent. The purpose of our study was to explore the relationship between low-level lead exposure from daily environmental contaminants and semen quality in a community population without occupational exposure. We recruited 751 students in the Male Reproductive Health in Chongqing College Students (MARHCS) study and 190 community males from Bishan, Chongqing. Eight urinary metals (Pb, Cd, As, Cu, Zn, Ni, Mn, and Cr), semen quality, and serum sex hormones were detected. Even if the blood lead concentration was below the US lead poisoning standard for children (100 µg/L), a significant dose-response relationship was found between lead exposure and a decrease in semen quality. Multilinear regression showed that urinary Pb was negatively associated with sperm concentration, total sperm count, progressive motility and total sperm motility (regression coefficient: -0.074, -0.103, -0.024, and -0.014, respectively; p: <0.001, <0.001, 0.007, and <0.001, respectively), accompanied by decreased serum follicle-stimulating hormone, serum testosterone and the testosterone/luteinizing hormone ratio (ß coefficient: -0.090, -0.082, and -0.020, respectively; p: 0.002, <0.001, and 0.021, respectively). Logistic regression also indicated that the risk of having abnormal semen quality was higher in the high Pb group (OR: 2.501, 95% CI: 1.411, 4.435, p = 0.002) than in the low Pb group after adjusting for confounders, with a dose-response relationship in the trend test (p = 0.007). Our results revealed an inverse association between Pb exposure at low levels and semen quality.

The prevalence and persistence of aberrant promoter DNA methylation in benzene-exposed Chinese workers.

Aberrant DNA methylation patterns are common in cancers and environmental pollutant exposed subjects. Up to date, few studies have examined the aberrant DNA methylation patterns in benzene exposed workers. We recruited 141 benzene-exposed workers, including 83 benzene-exposed workers from a shoe factory in Wenzhou and 58 workers from a painting workshop in Wuhu, 35 workers in Wuhu were followed from 2009 to 2013, and 48 indoor workers as controls from Wenzhou. We used high-resolution melting (HRM) to quantitate human samples of DNA methylation in long interspersed nuclear element-1 (LINE-1), (6)-methylguanine-DNA methyltransferase (MGMT), and DNA mismatch repair gene human mutator L homologue 1 (hMLH1). AML-5 cells were treated with benzoquinone (BQ) and hydroquinone (HQ), and the promoter methylation of MGMT and hMLH1 was detected using the bisulfite sequencing PCR method. The degree of LINE-1 methylation in benzene-exposed workers was significantly lower than that of the controls (p<0.001), and the degree of MGMT (p<0.001) and hMLH1 (p = 0.01) methylation was significantly higher than that of the controls. The in vitro study validated the aberrant hypermethylation of hMLH1 after treatment with BQ. Among the cohort workers who were followed from 2009 to 2013, the LINE1 methylation elevated in 2013 than 2009 (p = 0.004), and premotor methylation in hMLH1 reduced in 2013 than 2009 (p = 0.045) with the reduction of the benzene exposure. This study provides evidence that benzene exposure can induce LINE-1 hypomethylation and DNA repair gene hypermethylation.

Identification of immune and metabolic predictors of severe hand-foot-mouth disease.

Hand, foot and mouth disease (HFMD) is an infectious disease that affects mostly children. The children with HFMD also have other immune and metabolic disorders. However, the association of these disorders with the severity of HFMD has not yet been determined. In this study, we used a case-control study design to examine the correlation of immune and metabolic disorders with HFMD development in children. 406 mild and severe patients were recruited and divided into different subgroups based on the number of days from the initial onset time to hospitalization (1, 2, 3, 4, and ≥5 days). Logistic regression model was used to define the predictors of severe HFMD. We found that the patients from rural area (OR = 1.76, 95% CI [1.19~2.63], P = 0.005) or with body temperature of >39°C (OR = 2.14, 95% CI [1.12~4.12], P = 0.022) exhibited higher risk for severe symptoms. In addition, the risk increased with the rise of body temperature by using a Chis-quare trend test (P = 0.01). We also found that a decreased number of eosinophils was an predictor of severe HFMD at 1, 2, 3,and 4 days post infection (dpi). Decreased levels of Na+, Cl-, and creatine kinase were also predictors at 1 and ≥5 dpi. On the other hand, elevated level of globulin was a predictor for severe HFMD at 4 dpi and ≥5 dpi, and the increased number of neutrophils or increased level of alkaline phosphatase posed risk for severe HFMD at 3 and ≥5 dpi. Our results suggested that rural living, hyperpyrexia, changes in the immune system that include the numbers of eosinophils and neutrophils and the levels of IgG and globulin, and metabolic alterations, such as the levels of alkaline phosphatase, Na+, Cl-, and creatine kinase in peripheral blood are predictors of severe HFMD.

Association of BER and NER pathway polymorphism haplotypes and micronucleus frequencies with global DNA methylation in benzene-exposed workers of China: Effects of DNA repair genes polymorphisms on genetic damage.

OBJECTIVE: The base excision repair (BER) pathway and nucleotide excision repair (NER) pathway play important roles in the repair of benzene-induced genetic damage, and the effects of polymorphisms in these pathways on genetic damage and global DNA methylation are of great interest. METHODS: Ten single nucleotide polymorphisms (SNPs) in the BER (XRCC1: rs25489, rs25487; APE1: rs1130409) and NER pathways (XPA: rs1800975; XPC: rs2228000, rs2228002; XPD: rs13181, rs1799793; XPG: rs17655; ERCC1: rs3212986) were analyzed by a Kompetitive allele-specific PCR (KASP) assay to find associations with cytokinesis-block micronucleus (MN) frequency and global DNA methylation in 294 shoe factory workers and 102 control participants. RESULTS: Workers who possessed the following genotypes were associated with high MN frequency: rs25487 AA (FR (95% CI): 1.50 (1.16,1.9), p = 0.002, reference GG); rs1130409 GG (FR (95% CI): 1.28 (1.05,1.55), p = 0.010, reference TT); rs17655 GC (FR (95% CI): 1.18 (1.02,1.38), p = 0.038, reference GG); and rs3212986 TT (FR (95% CI): 1.55 (1.31,1.83), p < 0.001, reference GG). Workers with four and three mutant alleles showed 3.72-fold (OR (95% CI): 3.72 (1.34, 10.03), p = 0.009) and 2.48-fold (OR (95% CI): 2.48 (1.27, 4.88), p = 0.008) increased risk of genetic damage compared with workers with no or one mutant allele, and a dose-response relationship was found by the trend test (p = 0.006). The rs1130409 variant allele (GG+GT) was associated with low global DNA methylation (ß=-0.20, 95% CI: -0.42, 0.03, p = 0.045). CONCLUSION: In benzene-exposed workers, BER and NER pathway polymorphism haplotypes are associated with different levels of chromosome damage and had little effect on global DNA methylation.

Mast cells contribute to Enterovirus 71 infection-induced pulmonary edema in neonatal mice.

Enterovirus (EV) 71 infection has been widely acknowledged as the leading cause of severe hand, foot and mouth disease (HFMD), which may rapidly lead to fatal pulmonary edema. In this study, we established a mouse model for EV71 infection exhibiting high incidence of severe symptoms with pulmonary edema. Mast cells (MCs) accumulation, activation and allergic inflammation were found in the brains, lungs and skeletal muscle of mice after EV71 infection, especially in the lungs of mice. Levels of histamine, platelet-activating factor (PAF), interleukin (IL)-4, IL-5, IL-13, tumor necrosis factor-α (TNF-α), nitric oxide (NO), endocrine gland-derived vascular endothelial growth factor (EG-VEGF) and noradrenaline (NA) were increased in EV71-infected lungs. In addition, EV71 infection reduced the number of pulmonary T cells, dendritic cells (DCs) and monocytes, and increased the number of lung eosinophils, Tregs and MCs. MCs number and tryptase expression in target organs or tissues posed a trend towards an increase from control to severe mice. There were positive correlations between MCs number in the brains (r = 0.701, P = 0.003), lungs (r = 0.802, P < 0.0001), skeletal muscles (r = 0.737, P = 0.001) and mean clinical score. Thus, our results suggested that MCs contributed to the pulmonary edema during EV71 infection.

Involvement of the renin-angiotensin system in the progression of severe hand-foot-and-mouth disease.

BACKGROUND: Hand-foot-and-mouth disease (HFMD) is generally considered as a mild exanthematous disease to infants and young children worldwide. HFMD cases are usually mild and self-limiting but for few cases leads to complicated severe clinical outcomes, and even death. Previous studies have indicated that serum Ang II levels in patients with H7N9 infection were related to the severity of infection. However, the mechanisms underlying the pathogenesis of severe HFMD remain unclear. This study was undertaken to clarify the role of the renin-angiotensin system (RAS) in the progression of severe HFMD. METHODS: In the present study, 162 children including HFMD patients and healthy controls were recruited. The data was analyzed by time-series fashion. Concentrations of angiotensin II (Ang II) and noradrenaline (NA) in serum of patients were measured with ELISA. We established a mouse model for enterovirus 71 (EV71) infection and determined concentrations of Ang II, NA in tissue lysates at 3, 5 and 7 days post infection (dpi). RESULTS: The concentrations of Ang II and NA in serum of the HFMD patients with mild or severe symptoms were significantly higher than that in healthy controls. Additionally, the concentrations of Ang II and NA in serum of severe cases were significantly higher than those mild cases and the increased concentrations of Ang II and NA showed the same time trend during the progression of HFMD in the severe cases. Furthermore, the concentrations of Ang II and NA in target organs of EV71-infected mice including brains, skeletal muscle, and lungs were increased with the progression of EV71 infection in mice. Histopathological alterations were observed in the brains, skeletal muscle and lungs of EV71-infected mice. CONCLUSION: Our study suggested that activation of the RAS is implicated in the pathogenesis of severe HFMD.

MTHFR Gene Polymorphism Is Associated With DNA Hypomethylation and Genetic Damage Among Benzene-Exposed Workers in Southeast China.

OBJECTIVE AND METHODS: To analyze the association between global DNA methylation and single-nucleotide polymorphisms (SNPs) in methylenetetrahydrofolate reductase (MTHFR). MTHFR polymorphisms rs1801133 and rs1801131 were detected using the restriction fragment length polymorphism method, and cytokinesis-block micronucleus (MN) frequency and global DNA methylation was measured in workers from 410 shoe factories. RESULTS: A multilinear regression analysis demonstrated that DNA methylation of the TT variant allele of rs1801133 was lower than that of the CC wild type allele (Exp(ß) [95% CI], 0.76 [0.56, 1.02], P = 0.071), with a P-value approaching significance. A significantly increased MN frequency was observed for carriers of the TT genotype (frequency ratio = 1.27, 95% CI: 1.07-1.51, P < 0.01). CONCLUSION: The results imply that the TT genotype in rs1801133 is associated with global DNA hypomethylation, which may influence the induction of MN following exposure to benzene.