Ambient nitrogen dioxide and cardiovascular diseases in rural regions: a time-series analyses using data from the new rural cooperative medical scheme in Fuyang, East China.

Most of studies relating ambient nitrogen dioxide (NO2) exposure to hospital admissions for cardiovascular diseases (CVDs) were conducted among urban population. Whether and to what extent these results could be generalizable to rural population remains unknown. We addressed this question using data from the New Rural Cooperative Medical Scheme (NRCMS) in Fuyang, Anhui, China. Daily hospital admissions for total CVDs, ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke in rural regions of Fuyang, China, were extracted from NRCMS between January 2015 and June 2017. A two-stage time-series analysis method was used to assess the associations between NO2 and CVD hospital admissions and the disease burden fractions attributable to NO2. In our study period, the average number (standard deviation) of hospital admissions per day were 488.2 (117.1) for total CVDs, 179.8 (45.6) for ischaemic heart disease, 7.0 (3.3) for heart rhythm disturbances, 13.2 (7.2) for heart failure, 267.9 (67.7) for ischaemic stroke, and 20.2 (6.4) for haemorrhagic stroke. The 10-µg/m3 increase of NO2 was related to an elevated risk of 1.9% (RR: 1.019, 95% CI: 1.005 to 1.032) for hospital admissions of total CVDs at lag0-2 days, 2.1% (1.021, 1.006 to 1.036) for ischaemic heart disease, and 2.1% (1.021, 1.006 to 1.035) for ischaemic stroke, respectively, while no significant association was observed between NO2 and hospital admissions for heart rhythm disturbances, heart failure, and haemorrhagic stroke. The attributable fractions of total CVDs, ischaemic heart disease, and ischaemic stroke to NO2 were 6.52% (1.87 to 10.94%), 7.31% (2.19 to 12.17%), and 7.12% (2.14 to 11.85%), respectively. Our findings suggest that CVD burdens in rural population are also partly attributed to short-term exposure to NO2. More studies across rural regions are required to replicate our findings.

Selenium attenuates the association of co-exposure to arsenic, cadmium, and lead with cognitive function among Chinese community-dwelling older adults.

The effects of interactions between the toxic and essential metal mixtures on cognitive function are poorly understood. This study aims to identify the joint association of arsenic (As), cadmium (Cd), and lead (Pb) with cognitive function in older adults and the moderating role of selenium (Se), zinc (Zn), and copper (Cu) in this association. This study included 1000 community-dwelling older adults. Cognitive function was assessed by the Mini-Mental State Examination (MMSE). Blood concentrations of As, Cd, Pb, Se, Zn, and Cu were measured using inductively coupled plasma mass spectrometry. Linear regression and Bayesian kernel machine regression (BKMR) models were applied to assess the individual and joint associations of As, Cd, and Pb with cognitive function and to examine whether Se, Zn, and Cu (individually and as a mixture) modified these associations. In the adjusted single-metal models, both Cd (ß = - 0.37, 95% CI: - 0.73 to - 0.01) and Pb (ß = - 0.44, 95% CI: - 0.86 to - 0.02) were associated with MMSE scores, while Se (ß = 0.71, 95% CI: 0.30 to 1.13) exhibited a positive relationship with MMSE scores. Univariate exposure-response functions from BKMR models showed similar results. Moreover, the toxic metal mixture (As, Cd, and Pb) exhibited a significant negative association with MMSE scores in a dose-response pattern, with Pb being the greatest contributor within the mixture. The negative association of Pb alone or the toxic metal mixture with MMSE scores became weaker at higher concentrations of Se within its normal range, especially when Se levels were greater than the median (89.18 µg/L). Our findings support that Se can attenuate the negative associations of exposure to single Pb or the As, Cd, and Pb mixtures with cognitive function. Future prospective studies are needed to replicate our findings.

The association between essential trace element mixture and atherosclerotic cardiovascular disease risk among Chinese community-dwelling older adults.

The evidence about the association of the essential trace element (ETE) mixture with atherosclerotic cardiovascular disease (ASCVD) amongst older adults is limited. This study aims to evaluate the associations of single ETEs and the ETE mixture with the 10-year ASCVD risks and its predicting factors in Chinese community-dwelling older adults. A total of 607 community-dwelling older adults were included in this study. Blood levels of vanadium (V), chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), and selenium (Se) were assessed by inductively coupled plasma mass spectrometry. The predicted 10-year ASCVD risk was calculated using the Prediction for ASCVD Risk in China (China-PAR) equations. Traditional linear regressions and Bayesian kernel machine regression (BKMR) were used to assess the associations of single ETEs and the ETE mixture with the 10-year ASCVD risks and its predicting factors such as systolic blood pressure (SBP), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), diabetes, and waist circumference (WC). In linear regression models, blood Cr levels were negatively associated with the 10-year ASCVD risks after adjustment for covariates (ß = - 0.07, 95% CI = - 0.11 ~ - 0.03); The 3th quartile (Q3) of Se levels was also associated with a lower 10-year ASCVD risks when compared with the lowest quartile (Q1) of Se levels (ßQ3 vs. Q1: - 0.12, 95% CI = - 0.22 ~ - 0.02). In BKMR models, the negative associations of Cr and Se with the 10-year ASCVD risks were observed. Higher blood levels of ETE mixture were associated with decreased 10-year ASCVD risks in a dose-response pattern, with Cr having the highest value of the posterior inclusion probability (PIP) within the mixture. Furthermore, a positive association between Cr and HDL-C and a negative association between Se and SBP were found in both linear regression and BKMR models. Cr and Se were negatively associated with the 10-year ASCVD risks, individually and as a mixture. ETE mixture showed a linear dose-response association with decreased 10-year ASCVD risks, with Cr being the most important component within the mixture. The negative association of the ETE mixture with the 10-year ASCVD risks may be attributed to Cr and Se, mainly mediated by HDL-C and SBP, respectively. Further cohort studies are needed to clarify this association.

An adaptive enhancement method for breast X-ray images based on the nonsubsampled contourlet transform domain and whale optimization algorithm.

We propose a new method for breast X-ray image adaptive enhancement that combines nonsubsampled contourlet transform (NSCT) with the whale optimization algorithm (WOA). First, the mammography X-ray image was processed by histogram equalization to ensure global image contrast. The processed image was then decomposed into three layers in the NSCT domain. Each layer was each decomposed into two, four, and eight directions. A median filter was used to remove noise in the first and second layers. Then, a special edge filter was adopted to enhance each sub-band image, and two parameters are involved. WOA is used to automatically search the optimal two parameters. Blind image quality index (BIQI) adaptive function was used as an objective function of WOA. Then, inverse NSCT was employed to reconstruct the processed image, generating the final adaptive enhancement image. The digital database for screening mammography (DDSM) was used to verify the performance of the proposed method. Five objective evaluation indexes, including information entropy, average gradient, standard deviation, contrast improvement index (CII), and BIQI, are combined together to construct a new comprehensive index to evaluate the visual quality of the enhanced image. The results show that the proposed method has a good enhancement effect for mammography X-ray images. The overall performance of the proposed method is better than some existing similar methods. Graphical abstract .