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Background and aims The association between isoflavone (ISF) consumption and cardiovascular disease (CVD) remains controversial because of limited evidence. Carotid atherosclerosis is an established indicator of subclinical CVD. The study aimed to investigate the relationship between dietary ISF intake and subclinical CVD in middle-aged and elderly adults. Methods and results A total of 873 subjects aged 40–70 years without CVD were enrolled in this cross-sectional study. A restricted cubic spline was used to investigate the association between ISF intake and subclinical CVD risk. The odds ratio (OR) and 95% confidence interval of the risk of subclinical CVD for ISF were estimated by two-segmented logistic regression analysis. In Model 2, there was a non-linear association between ISF intake and the risk of subclinical CVD among women (Pnon-linear = 0.002), with an inverse association below the change point. The nadir for the risk of subclinical CVD among women was 7.26 mg/day (energy-adjusted). Below the change point, an increase of 1 mg ISF/day reduced the risk of subclinical CVD by 15%. There was no significant association between ISF intake and subclinical CVD risk above the change point (OR = 1.01 [0.99, 1.04]). ISF intake was not associated with subclinical CVD risk in men (Model 2: Pnon-linear = 0.224). Conclusions Below the change point (7.26 mg/day), women with a higher intake of ISF had a significantly lower risk of subclinical CVD. Encouraging the consumption of ISF-rich foods may help to lower CVD risk in middle-aged and elderly women. Trial registration This study is registered at http://www.chictr.org.cn (ChiCTR 1900022445).

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (5 cm). Researchers have attempted to estimate root-zone soil moisture using multiple regression, data assimilation, and data-driven methods. However, correlations between root-zone soil moisture and its related variables, including surface soil moisture, always appear nonlinear, which is difficult to extract and express using typical statistical methods. The artificial intelligence (AI) method, which is advantageous for nonlinear relationship analysis and extraction is applied for root-zone soil moisture estimation, but by only considering its separate temporal or spatial correlations. The convolutional long short-term memory (ConvLSTM) model, known to capture spatiotemporal patterns of large-scale sequential datasets with the advantage of dealing with spatiotemporal sequence-forecasting problem, was used in this study to estimate root-zone soil moisture based on remote sensing-based variables. Owing to limitation of regional soil moisture observation data, the physical model Hydrus-1D was used to generate large and spatiotemporal vertical soil moisture dataset for the ConvLSTM model training and verification. Then, normalized difference vegetation index (NDVI) etc. remote sensing-based factors were selected as predictive variables. Results of the ConvLSTM model showed that the fitting coefficients (R

The rapid economic and population growth in coastal areas is causing increasingly serious polycyclic aromatic hydrocarbons (PAHs) pollution in these regions. This review compared the PAHs pollution characteristics of different coastal areas, including industrial zones, commercial ports, touristic cities, aquacultural & agricultural areas, oil & gas exploitation areas and megacities. Currently there are various treatment methods to remediate soils and sediments contaminated with PAHs. However, it is necessary to provide a comprehensive overview of all the available remediation technologies up to date, so appropriate technologies can be selected to remediate PAHs pollution. In view of that, we analyzed the characteristics of the remediation mechanism, summarized the remediation methods for soil or sediments in coastal areas, which were physical repair, chemical oxidation, bioremediation and integrated approaches. Besides, this review also reported the development of new multi-functional green and sustainable systems, namely, micro-nano bubble (MNB), biochar, reversible surfactants and peracetic acid. While physical repair, expensive but efficient, was regarded as a suitable method for the PAHs remediation in coastal areas because of land shortage, integrated approaches would produce better results. The ultimate aim of the review was to ensure the successful restructuring of PAHs contaminated soil and sediments in coastal areas. Due to the environment heterogeneity, PAHs pollution in coastal areas remains as a daunting challenge. Therefore, new and suitable technologies are still needed to address the environmental issue.

Sleep disturbance, anxiety, and depression are frequently observed in cancer patients. There have fewer studies about the sleep and emotional status of nasopharyngeal carcinoma (NPC) patient family caregivers (FCs) before treatment. We explored the sleep, depression, and anxiety in NPC patient FCs before therapy, compared sleep quality between caregivers with and without depression and anxiety, and examined and related factors of sleep disturbance in FCs of NPC patients before therapy. FC-patient dyads included from two centers were 92 in total. The proportions of poor sleep, anxiety, and depression in NPC patient FCs were 45.7%, 43.5%, and 54.3%, respectively. FCs with anxiety or depression were more inclined to report decreased sleep quality. Depressed caregivers were 11.11 times more to be poor quality sleep before patients treatment (OR = 11.11, 95%; CI = 2.94-42.05). NPC patient FCs before treatment are at high risk of sleep disturbances, depression, and anxiety, especially those already experiencing anxiety and depression symptoms.

Inflammation and obesity are the main risk factors for the development of carotid atherosclerosis and atherosclerotic cardiovascular disease (ASCVD). The neutrophil-to-lymphocyte ratio (NLR) is a recently developed indicator of inflammation that can be easily calculated from blood cell counts. The Chinese Visceral Adiposity Index (CVAI) was used to assess visceral obesity in the Chinese population.To explore the associations between both NLR and CVAI, and carotid atherosclerosis and ASCVD risk in elderly Chinese.A total of 4437 participants aged ≥55 years and with no history of cardiovascular disease, were enrolled in this retrospective study. Anthropometric measurements, laboratory results, and carotid ultrasonography results were extracted from a database. We used established formulas to calculate NLR and CVAI, and the Pooled Cohort Equations to generate the 10-year ASCVD risk score. Participants were divided into two groups according to their 10-year ASCVD scores:7.5% and ≥7.5%.NLR and CVAI were significantly higher in patients with carotid atherosclerosis. Regression analysis showed that NLR (OR 1.23, 95% CI 1.05-1.43, p = 0.01) and CVAI (OR 1.39, 95% CI 1.21-1.61, p = 0.001) were independent risk factors for carotid atherosclerosis. A combination of NLR and CVAI improved the goodness-of-fit (p 0.001) and discriminability of the model (p = 0.0013). NLR, CVAI and carotid plaques showed positive associations with the 10-year ASCVD risk score (all p 0.001).NLR and CVAI are positively associated with the prevalence of carotid atherosclerosis and high risk of ASCVD in elderly adults and could be useful in the identification of a high risk of atherosclerosis.