Assessing spatiotemporal risks of nonpoint source pollution via soil erosion: a coastal case in the Yellow River Delta, China.

Nonpoint source pollution (NPSP) has always been the dominant threat to regional waters. Based on empirical models of the revised universal soil loss equation and the phosphorus index, an NPSP risk assessment model denoted as SL-NPSRI was developed. The surface soil pollutant loss was estimated by simulating the rain-runoff topographic process, and the influence of path attenuation was quantified. A case study in the Yellow River Delta and corresponding field surveys of soil pollutants and water quality showed that the established model can be applied to evaluate the spatial heterogeneity of NPSP. NPSP usually occurs during high-intensity rainfall periods and in larger estuaries. Summer rainfall increased pollutant transport into the sea from late July to mid-August and caused estuarine dilution. Higher NPSP risks often correspond to coastal areas with lower vegetation coverage, higher soil erodibility, and higher soil pollutant concentrations. Agricultural NPSP originating from cropland significantly increase the pollutant fluxes. Therefore, area-specific land use management and vegetation coverage improvement, and temporal-specific strategies can be explored for NPSP control during source-transport hydrological processes. This research provides a novel insight for coastal NPSP simulations by comprehensively analyzing the soil erosion process and its associated pollutant loss effects, which can be useful for targeted spatiotemporal solutions.

Spatiotemporal dynamics of wetlands and their future multi-scenario simulation in the Yellow River Delta, China.

Wetlands, known as the "kidney of the earth", are an important component of global ecosystems. However, they have been changed under multiple stresses in recent decades, which is especially true in the Yellow River Delta. This study examined the spatiotemporal change characteristics of wetlands in the Yellow River Delta from 1980 to 2020 and predicted detailed wetland changes from 2020 to 2030 with the patch-generating land use simulation (PLUS) model under four scenarios, namely, the natural development scenario (NDS), the farmland protection scenario (FPS), the wetland protection scenario (WPS) and the harmonious development scenario (HDS). The results showed that wetlands increased 709.29 km2 from 1980 to 2020 overall, and the wetland types in the Yellow River Delta changed divergently. Over the past four decades, the tidal flats have decreased, whereas the reservoirs and ponds have increased. The gravity center movement of wetlands differed among the wetland types, with artificial wetlands moving to the northwest and natural wetlands moving to the south. The movement distance of the gravity center demonstrated apparent phase characteristics, and an abrupt change occurred from 2005 to 2010. The PLUS model was satisfactory, with an overall accuracy (OA) value greater than 83.48 % and an figure of merit (FOM) value greater than 0.1164. From 2020 to 2030, paddy fields and tidal flats decreased, whereas natural water, marshes and reservoirs and ponds increased under the four scenarios. The WPS was a relatively ideal scenario for wetlands, and the HDS was an alternative scenario for wetland restoration and food production. In the future, more attention should be paid to restoring natural wetlands to prevent further degradation in the Yellow River Delta. This study provides insights into new understandings of historical and future changes in wetlands and may have implications for wetland ecosystem protection and sustainable development.

[Estimation of Agricultural Non-point Source TN and TP Export Coefficients Based on Soil Loss].

Taking the Yellow River Delta as a typical research area, we constructed a coastal agricultural TN and TP non-point source pollution estimating model by analyzing the relationship between the surface soil pollutant loss risks and the monitored pollutant flux into the sea. On this basis, TN and TP non-point source export coefficients of paddy fields, irrigated land, and dry land were calculated, and the verification showed that the estimated export coefficients were acceptable. In the study area, the TN and TP export coefficients into the sea of arable land were 18.33 kg·(hm2·a)-1 and 1.02 kg·(hm2·a)-1, respectively. The agricultural non-point source pollution loads of arable land were relatively high in summer. The sub-basins with larger agricultural non-point source pollution loads were mainly located in the control areas of the Zhimai River, Guangli River, and Xiaodao River. The administrative regions with larger total agricultural TN and TP loads were mainly in the northern Huanghekou Town and Yong'an Town, and areas with larger loads per unit area were in the southwest. Therefore, it is necessary to pay more attention to the temporal effects of agricultural non-point source pollution, simultaneously coordinate the social and economic development, and formulate comprehensive agricultural non-point source pollution prevention and control strategies from the perspective of sub-basins and administrative units. This will allow us to improve the offshore pollution status from the perspective of land and sea coordination.

Ampelopsin Inhibits Cell Viability and Metastasis in Renal Cell Carcinoma by Negatively Regulating the PI3K/AKT Signaling Pathway.

BACKGROUND: Previous studies have shown that Ampelopsin has an inhibitory effect on human tumors. However, the effect of Ampelopsin on renal cell carcinoma (RCC) is rarely reported. Therefore, this study aims to explain the role of Ampelopsin in RCC. METHODS: Different concentrations of Ampelopsin (0, 10, 25, 50, and 100 µM) were used to treat 786-O cells. Cell viability was detected by MTT assay, colony formation assay, and flow cytometry assay. Transwell assay and Wound healing assay were used to detect cell migration and invasion. Western blot analysis was applied to detect protein expression. RESULTS: Ampelopsin inhibited cell proliferation and induced apoptosis in RCC. And Ampelopsin can inhibit cell migration and invasion in RCC. All these results changed in a dose-dependent manner. Ampelopsin (100 uM) had the strongest inhibitory effect on cell viability and metastasis. In addition, Ampelopsin negatively regulated the PI3K/AKT signaling pathway in RCC cells. Moreover, Ampelopsin was only cytotoxic to RCC cells. CONCLUSION: Ampelopsin inhibits cell viability and metastasis in RCC by negatively regulating the PI3K/AKT signaling pathway.

Modified Renshen Wumei Decoction Alleviates Intestinal Barrier Destruction in Rats with Diarrhea.

Modified Renshen Wumei decoction (MRWD), a famous traditional Chinese medicine, is widely used for treating persistent diarrhea. However, as the mechanism by which MRWD regulates diarrhea remains unknown, we examined the protective effects of MRWD on intestinal barrier integrity in a diarrhea model. In total, 48 male rats were randomly distributed to four treatment groups: the blank group (CK group), model group (MC group), Medilac-Vita group (MV group) and Chinese herb group (MRWD group). After a 21-day experiment, serum and colon samples were assessed. The diarrhea index, pathological examination findings and change in D-lactate and diamine oxidase (DAO) contents illustrated that the induction of diarrhea caused intestinal injury, which was ameliorated by MV and MRWD infusion. Metabolomics analysis identified several metabolites in the serum. Some critical metabolites, such as phosphoric acid, taurine, cortisone, leukotriene B4 and calcitriol, were found to be significantly elevated by MRWD infusion. Importantly, these differences correlated with mineral absorption and metabolism and peroxisome proliferator-activated receptor (PPAR) pathways. Moreover, it significantly increased the expression levels of TLR4, MyD88 and p-NF-κB p65 proteins and the contents of IL-1 and TNF-α, while the expression levels of occludin, claudin-1 and ZO-1 proteins decreased. These deleterious effects were significantly alleviated by MV and MRWD infusion. Our findings indicate that MRWD infusion helps alleviate diarrhea, possibly by maintaining electrolyte homeostasis, improving the intestinal barrier integrity, and inhibiting the TLR4/NF-κB axis.

Using soil erosion to locate nonpoint source pollution risks in coastal zones: A case study in the Yellow River Delta, China.

Soil erosion contributes greatly to nonpoint source pollution (NSP). We built a coastal NSP risk calculation method (CNSPRI) based on the Revised Universal Soil Loss Equation (RUSLE) and geospatial methods. In studies on the formation and transport of coastal NSP, we analysed the pollution impacts on the sea by dividing subbasins into the sea and monitoring the pollutant flux. In this paper, a case study in the Yellow River Delta showed that the CNSPRI could better predict the total nitrogen (TN) and total phosphorus (TP) NSP risks. The value of the soil erodibility factor (K) was 0.0377 t h·MJ-1·mm-1, indicating higher soil erodibility levels, and presented an increased trend from the west to the east coast. The NSP risk also showed an increased trend from west to east, and the worst status was found near the Guangli River of the south-eastern region. The contributions of the seven influencing factors to CNSPRI presented an order of vegetation cover > rainfall erosivity > soil content > soil erodibility > flow > flow path > slope. The different roles of source and sink landscapes influenced the pollutant outputs on a subbasin scale. Arable land and saline-alkali land were the two land-use types with the greatest NSP risks. Therefore, in coastal zones, to reduce NSP output risks, we should pay more attention to the spatial distribution of vegetation cover, increase its interception effect on soil loss, and prioritize the improvement of saline-alkali land to reduce the amount of bare land.

Studies on the Spatiotemporal Variability of River Water Quality and Its Relationships with Soil and Precipitation: A Case Study of the Mun River Basin in Thailand.

Human activities can affect soil nutrients, thereby influencing river water quality. The spatial pattern of precipitation also impacts distributions of water quality. In this paper, we employed a method that combines point survey, soil, and water quality data to analyze the spatial relationships between precipitation, soil nutrient and water quality in the basin on the basis of field surveys and laboratory analysis. The ordinary kriging method was applied to interpolate the precipitation and soil data, and the spatial pattern was analyzed. The water samples on the main stream and soil samples in the field were collected during both the dry and rainy seasons to analyze the water quality and soil nutrients. The results indicate: (1) The water quality in the dry season is better than that in the rainy season, the water quality in the upper reaches is better than that in the lower reaches, and agricultural activity is the direct source of water pollution. (2) The precipitation in the rainy and dry seasons is differente and the dilution effect of precipitation on pollutant concentrations and transport of water flow affect the spatial distribution of water quality. (3) There is a significant difference in the spatial pattern of soil nutrients between the dry and rainy seasons, and the soil nutrient content and the surface runoff directly affect the water quality. Soil nutrients are affected by human activities, and they potentially act as nonpoint source (NPS) pollution in this river basin. To improve the water quality, suitable agriculture measures need to be implemented.

Distribution Characteristics and Seasonal Variation of Soil Nutrients in the Mun River Basin, Thailand.

Based on soil sampling data from the dry season and the rainy season, the spatial heterogeneity and spatial pattern of soil nutrients in the Mun River Basin, Thailand, were studied and the seasonal variation in soil nutrients was analyzed using classical statistical methods and geostatistical methods. The soil nutrient content in the Mun Basin showed moderate and strong variations, and the descending order of soil variability was as follows: available phosphorous (AP) > electric conductivity (EC) > soil organic matter (SOM) > total nitrogen (TN) > pH value in the dry season, with AP showing strong variation, and EC > AP > SOM > TN > pH in the rainy season, with EC showing strong variation. Different soil nutrients and different soil properties had different spatial variation characteristics, and their corresponding best-fitting models were also different. Based on the nugget (C0), sill (C0 + C), and range (A), spatial analysis was performed for the soil nutrients, pH, and EC in the dry season and in the rainy season. Analysis based on kriging spatial interpolation data showed that pH, SOM, TN, and EC had convex or concave distributions, whereas AP had a patchy distribution. Terrain, vegetation, and human disturbance are the main factors that contribute to the differences in the soil nutrient pattern of the Mun River Basin.