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Objective: The atherogenic index of plasma (AIP), consisting of triglycerides and high-density lipoprotein cholesterol, is applied to estimate the cardiovascular disease risk. The evidence regarding the association between AIP and prehypertension or hypertension remains inconclusive. This study was conducted to investigate the association of AIP and prehypertension or hypertension in normoglycemic subjects in Japan., Methods: In the present cross-sectional study, 15,453 normoglycemic participants aged 18 years or older in Gifu, Japan, were evaluated. The selected participants were separated into four groups in the light of AIP quartiles, ranging from the lowest quartile (Q1) to the highest quartile (Q4). And the association between AIP and prehypertension or hypertension was explored with multivariate logistic regression by gradually adjusting model., Results: Among the 15,453 participants, aged of 43.7 ± 8.9 years, and of whom 45.5% were females, the prevalence rates of prehypertension or hypertension were 27.68% (4,278) and 6.23% (962) respectively. In multivariate logistic regression analyses, participants in the highest AIP quartile had an increase risk in prehypertension and hypertension, compared with participants the lowest one, the odds ratios (OR) were 1.15 (95%CI: 1.00-1.13, P = 0.045) for prehypertension and 1.54 (95%CI:1.16-2.04, P = 0.003) for hypertension after adjusting confounders. In subgroup analyses, the high risk of hypertension was also observed for female participants in the highest AIP quartile (Q4) (OR = 2.19, 95%CI: 1.37-3.49, P = 0.001), especially between the ages of 40 and 60 years (OR = 2.20, 95%CI: 1.24-3.88, P = 0.007)., Conclusions: Higher AIP is significantly and positively associated with the risk of prehypertension or hypertension in normoglycemic subjects in Gifu, Japan, which was more pronounced in the female population, especially between the years of 40 and 60., (© 2023. The Author(s).)

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging haemorrhagic fever that was first described in rural areas of China. The causative agent, SFTS virus (SFTSV), is a novel phlebovirus in the Bunyaviridae family. Since the first report in 2010, SFTS has been found in 11 provinces of China, with about 2500 reported cases, and an average case-fatality rate of 7·3%. The disease was also reported in Japan and Korea in 2012; Heartland virus, another phlebovirus genetically closely related to SFTSV, was isolated from two patients in the USA. The disease has become a substantial risk to public health, not only in China, but also in other parts of the world. The virus could undergo rapid evolution by gene mutation, reassortment, and homologous recombination in tick vectors and vertebrate reservoir hosts. No specific treatment of SFTS is available, and avoiding tick bites is an important measure to prevent the infection and transmission of SFTSV. This Review provides information on the molecular characteristics and ecology of this emerging tick-borne virus and describes the epidemiology, clinical signs, pathogenesis, diagnosis, treatment, and prevention of human infection with SFTSV., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

We present a spatiotemporal evaluation of water quality incidents in Japan considering incident numbers, incident causes, pollutant categories, and pollution effects. Water pollution incidents in first-class river systems almost tripled to about 1487 in the 12 years from 1996 to 2007. In addition, oil makes up the largest proportion of pollutants nationwide (76.61%) and the major source of pollution for each region in Japan. Moreover, every category shows a growth trend, especially since 2005. The main cause of incidents was "Unknown" (43%), followed by "Poor working practice" (24%), and then by "Accident" (10%) and "Other" (10%). In Hokuriku, however, the main cause of incidents was "Poor working practice" (36%), which is greater than "Unknown" (30%). Finally, waterworks (approximately 60%) was the largest of four kinds of water supply infrastructure affected by pollution incidents, followed by simplified waterworks. The population affected by offensive odors and tastes peaked in 1990 and has been decreasing. Overall, the results show the characteristics of incidents from 1996 to 2007, with significant implications for adaptation measures, strategies and policies to reduce water quality incidents., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Nutrients and suspended sediment in surface water play important roles in aquatic ecosystems and contribute strongly to water quality with implication for drinking water resources, human and environmental health. Estimating loads of nutrients (nitrogen and phosphorus) and suspended sediment (SS) is complicated because of infrequent monitoring data, retransformation bias, data censoring, and non-normality. To obtain reliable unbiased estimates, the Maintenance of Variance-Extension type 3 (MOVE. 3) and the regression model Load Estimator (LOADEST) were applied to develop regression equations and to estimate total nitrogen (TN), total phosphorus (TP) and SS loads at five sites on the Ishikari River, Japan, from 1985 to 2010. Coefficients of determination (R(2)) for the best-fit regression models for loads of TN, TP, and SS for the five sites ranged from 71.86% to 90.94%, suggesting the model for all three constituents successfully simulated the variability in constituent loads at all studied sites. Estimated monthly average loads at Yishikarikakou-bashi were larger than at the other sites, with TN, TP, and SS loads ranging from 8.52×10(3) to 2.00×10(5) kg/day (Apr. 1999), 3.96×10(2) to 5.23×10(4) kg/ day (Apr. 1999), and 9.21×10(4) to 9.25×10(7) kg/day (Sep. 2001), respectively. Because of variation in river discharge, the estimated seasonal loads fluctuated widely over the period 1985 to 2010, with the greatest loads occurring in spring and the smallest loads occurring in winter. Estimated loads of TN, TP, and especially SS showed decreasing trends during the study period. Accurate load estimation is a necessary goal of water quality monitoring efforts and the methods described here provide essential information for effectively managing water resources., (Copyright © 2013 Elsevier B.V. All rights reserved.)

We evaluate the spatiotemporal trends of recent suspended sediment conditions in Japanese rivers. Statistical and spatiotemporal trend analysis is conducted on the 92 major rivers in Japan based on water quality monitoring data from 1992 to 2005. The Mann-Kendall non-parametric method was used to investigate the spatial and temporal trends for the suspended sediment indicator. Results show that the mean concentration of suspended sediments in Japanese rivers has generally declined in recent years, although there are still water quality problems at some monitoring sites (Kanto, Chubu, Kinki and Kyushu regions). A positive relationship between observed yearly discharge and suspended sediment load was found. Land use maps with 100 meter spatial resolution were used to apply an empirical model and develop a regression model for estimating annual suspended sediment loads directly from land use and hydrologic data. Rivers were assigned to three groups according to statistical cluster analysis of suspended sediment (SS) concentration. The correlation between the simulation result from the empirical model and the observed data had R(2) values of 0.62 and 0.71 for groups 2 and 3, and the correlation between the simulation result from the regression model and the observed data had R(2) values of 0.48 and 0.34 for groups 2 and 3. Results show that the proposed simulation technique can be used to predict the pollutant loads to river basins in Japan. Results also suggest prioritization methods and strategies that policy-makers can use to address suspended sediment pollution in rivers and water quality management in general.

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.

Artificial Neural Network (ANN) is a flexible and popular tool for predicting the non-linear behavior in the environmental system. Here, the feed-forward ANN model was used to investigate the relationship among the land use, fertilizer, and hydrometerological conditions in 59 river basins over Japan and then applied to estimate the monthly river total nitrogen concentration (TNC). It was shown by the sensitivity analysis, that precipitation, temperature, river discharge, forest area and urban area have high relationships with TNC. The ANN structure having eight inputs and one hidden layer with seven nodes gives the best estimate of TNC. The 1:1 scatter plots of predicted versus measured TNC were closely aligned and provided coefficients of errors of 0.98 and 0.93 for ANNs calibration and validation, respectively. From the results obtained, the ANN model gave satisfactory predictions of stream TNC and appears to be a useful tool for prediction of TNC in Japanese streams. It indicates that the ANN model was able to provide accurate estimates of nitrogen concentration in streams. Its application to such environmental data will encourage further studies on prediction of stream TNC in ungauged rivers and provide a useful tool for water resource and environment managers to obtain a quick preliminary assessment of TNC variations., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Land cover changes around river basins have caused serious environmental degradation in global surface water areas, in which the direct monitoring and numerical modeling is inherently difficult. Prediction of pollutant loads is therefore crucial to river environmental management under the impact of climate change and intensified human activities. This research analyzed the relationship between land cover types estimated from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery and the potential annual pollutant loads of river basins in Japan. Then an empirical approach, which estimates annual pollutant loads directly from satellite imagery and hydrological data, was investigated. Six water quality indicators were examined, including total nitrogen (TN), total phosphorus (TP), suspended sediment (SS), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Dissolved Oxygen (DO). The pollutant loads of TN, TP, SS, BOD, COD, and DO were then estimated for 30 river basins in Japan. Results show that the proposed simulation technique can be used to predict the pollutant loads of river basins in Japan. These results may be useful in establishing total maximum annual pollutant loads and developing best management strategies for surface water pollution at river basin scale.