Effects of Crude Extract of Glycyrrhiza Radix and Atractylodes macrocephala on Immune and Antioxidant Capacity of SPF White Leghorn Chickens in an Oxidative Stress Model.

The natural edible characteristics of Chinese herbs have led more and more people to study them as an alternative product to antibiotics. In this study, crude extracts of Glycyrrhiza radix and Atractylodes macrocephala (abbreviated as GRAM) with glycyrrhizic acid content not less than 0.2 mg/g were selected to evaluate the effects of GRAM on the immune and antioxidant capacity of model animals. Thirty 21-day-old male Leghorn chickens were weighed and randomly assigned to one of three groups of ten animals each. The treatments comprised a control group (CON), in which saline was injected at day 31, day 33, and day 35, an LPS-treated group (LPS), in which LPS (0.5 mg/kg of BW) was injected at day 31, day 33, and day 35, and finally a GRAM and LPS-treated group, (G-L) in which a GRAM-treated diet (at GRAM 2 g/kg) was fed from day 21 to day 35 with LPS injection (0.5 mg/kg of BW) at day 31, day 33, and day 35. The results of diarrhea grade and serum antioxidant measurement showed that the LPS group had obvious diarrhea symptoms, serum ROS and MDA were significantly increased, and T-AOC was significantly decreased. The oxidative stress model of LPS was successfully established. The results of immune and antioxidant indexes showed that feeding GRAM significantly decreased levels of the pro-inflammatory factors TNF-α, IL-1ß, and IL-6 (p < 0.05) and significantly increased levels of the anti-inflammatory factors IL-4 and IL-10 and levels of the antioxidant enzymes GSH-Px and CAT (p < 0.05). GRAM resisted the influence of LPS on ileum morphology, liver, and immune organs and maintained normal index values for ileum morphology, liver, and immune organs. In summary, this study confirmed the antidiarrheal effect of GRAM, which improved the immune and antioxidant capacity of model animals by regulating inflammatory cytokine levels and antioxidant enzyme activity in poultry.

Root-mediated acidification, phosphatase activity and the phosphorus-cycling microbial community enhance phosphorus mobilization in the rhizosphere of wetland plants.

Rhizoremediation of wetland plants is an environmentally friendly strategy for sediment phosphorous (P) removal, the basic underlying principle of which is the complex interactions between roots and microorganisms. This study investigated the immobilization and mobilization mechanisms of P in the rhizosphere of wetland plants using high-resolution spatial visualization techniques and metagenomic sequencing. Two-dimensional visualization of the spatial distribution of P, iron (Fe) and manganese (Mn) indicated that the sequestration of Fe-oxides rather than Mn-oxides caused the depletion of labile P, resulting in an increase in the Fe-adsorbed P fraction. Plants altered the rhizospheric environments and P-cycling microbial community to mobilize low-availability P from sediments. Mineral P solubilization and organic P mineralization were enhanced by local acidification and increased phosphatase activity, respectively. Microbial P mobilization also increased with increasing relative abundances of P solubilization and mineralization genes (gcd and phnW) and decreasing P transportation genes (ugpA, ugpB, and pit) genes in the rhizosphere. These processes led to the remobilization of 10.04 % of inorganic P, and 15.23 % of organic P, in the rhizosphere during the incubation period. However, the resupply of P via the above processes did not compensate for the depletion of rhizospheric P via root uptake and mineral sequestration. Our results provide novel insights into the mechanisms of rhizospheric P cycling, which will help to inform future phytoremediation strategies.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area.

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

EXOSC10 is a novel hepatocellular carcinoma prognostic biomarker: a comprehensive bioinformatics analysis and experiment verification.

Background: Hepatocellular carcinoma (HCC) is a common malignant tumor. There are few studies on EXOSC10 (exosome component 10) in HCC; however, the importance of EXOSC10 for HCC remains unclear. Methods: In the study, the prognosis value of EXOSC10 and the immune correlation were explored by bioinformatics. The expression of EXOSC10 was verified by tissue samples from clinical patients and in vitro experiment (liver cancer cell lines HepG2, MHCC97H and Huh-7; normal human liver cell line LO2). Immunohistochemistry (IHC) was used to detect EXOSC10 protein expression in clinical tissue from HCC. Huh-7 cells with siEXOSC10 were constructed using lipofectamine 3000. Cell counting kit 8 (CCK-8) and colony formation were used to test cell proliferation. The wound healing and transwell were used to analyze the cell migration capacity. Mitochondrial membrane potential, Hoechst 33342 dye, and flow cytometer were used to detect the change in cell apoptosis, respectively. Differential expression genes (DEGs) analysis and gene set enrichment analysis (GSEA) were used to investigate the potential mechanism of EXOSC10 and were verified by western blotting. Results: EXOSC10 was highly expressed in tissues from patients with HCC and was an independent prognostic factor for overall survival (OS) in HCC. Increased expression of EXOSC10 was significantly related to histological grade, T stage, and pathological stage. Multivariate analysis indicated that the high expression level of EXOSC10 was correlated with poor overall survival (OS) in HCC. GO and GSEA analysis showed enrichment of the cell cycle and p53-related signaling pathway. Immune analysis showed that EXOSC10 expression was a significant positive correlation with immune infiltration in HCC. In vitro experiments, cell proliferation and migration were inhibited by the elimination of EXOSC10. Furthermore, the elimination of EXOSC10 induced cell apoptosis, suppressed PARP, N-cadherin and Bcl-2 protein expression levels, while increasing Bax, p21, p53, p-p53, and E-cadherin protein expression levels. Conclusions: EXOSC10 had a predictive value for the prognosis of HCC and may regulate the progression of HCC through the p53-related signaling pathway.

Spatially varying relationships of soil Se concentration and rice Se concentration in Guangxi, China: A geographically weighted regression approach.

In recent years, the biogeochemical behavior and environmental impact of Selenium (Se) on soil-plant systems have received widespread attention, and traditional statistical methods reveal generally positive correlations between rice Se and soil Se. However, that initial positive relationship may have been obscured by local external factors. Using local scale data from the geochemical evaluation of land quality project, this work employed geographically weighted regression (GWR) to examine the spatial variation of rice Se (as the dependent variable) and soil Se (as the independent variable) in Guangxi. Strong and weak correlation coefficients occur between rice Se and soil Se, thereby indicating that their relationships are spatially varying. Guangxi is characterized by significantly positive correlations in most areas, with weak correlations mostly found in the south-western and central-eastern regions. Areas with weak correlation can be divided into two patterns: high soil Se with low rice Se and high rice Se with low soil Se. The unique patterns are correlated with distinct natural factors, particularly the abundance of Fe-rich soils in the carbonate area; by contrast, sandstone areas in central Guangxi may have been affected by anthropogenic activities. To reveal the spatially varying relationships at the local scale, we employed GWR, an effective tool that allowed us to identify the association between environmental variables and influencing factors and explore spatially varying relationships between them. This study breaks through the existing understanding that soil Se is completely positively correlated with rice Se for the first time, and concludes that their correlation is spatially variable, providing an effective approach for the study of complex relationships.

Effects of Sihuang Zhili Granules on the Diarrhea Symptoms, Immunity, and Antioxidant Capacity of Poultry Challenged with Lipopolysaccharide (LPS).

A growing interest has been focused on Chinese herbs as alternatives to antimicrobial growth promoters, which are characterized by non-toxic side effects and drug resistance. The purpose of this study was to evaluate the effects of the Sihuang Zhili granule (abbreviated as Sihuang) on diarrhea, immunity, and antioxidation in poultry. Thirty male Leghorn chickens, aged 21 days, were randomly assigned to one of three groups with ten animals each. The control group (CON) received intraperitoneal saline injections, while the LPS-challenged group (LPS) and Sihuang intervention group (SH) received intraperitoneal injections of LPS (0.5 mg/kg of BW) and Sihuang (5 g/kg) at d 31, d 33, d 35, respectively. The control and LPS groups were fed a basal diet, while the SH group was fed a diet supplemented with Sihuang from d 21 to d 35. Analysis of the diarrhea index showed that the addition of Sihuang inhibited the increase in the diarrhea grade and the fecal water content caused by LPS, effectively alleviating poultry diarrhea symptoms. The results of the immune and antioxidant indexes showed that Sihuang significantly reduced the contents of the pro-inflammatory factors TNF- α and IL-1 ß, as well as the oxidative stress markers ROS and MDA. Conversely, it increased the contents of the anti-inflammatory factors IL-4 and IL-10, along with the activities of antioxidant enzymes GSH-Px and CAT, thereby enhancing the immune and antioxidant abilities of chickens. Furthermore, Sihuang protected the chicken's ileum, liver, and immune organs from LPS invasion and maintained their normal development. In conclusion, this study confirmed the antidiarrheal effect of Sihuang in poultry farming and demonstrated its ability to improve poultry immunity and antioxidant capacity by modulating antioxidant enzyme activity and inflammatory cytokine levels.

DNAJ heat shock protein family member C1 can regulate proliferation and migration in hepatocellular carcinoma.

Background: DNAJ heat shock protein family (Hsp40) member C1(DNAJC1) is a member of the DNAJ family. Some members of the DNAJ gene family had oncogenic properties in many cancers. However, the role of DNAJC1 in hepatocellular carcinoma (HCC) was unclear. Methods: In this study, expression and prognostic value of DNAJC1 in HCC were analyzed by bioinformatics. Quantitative real-time PCR and Western blotting were used to verify DNAJC1 expression in liver cancer cell lines. Furthermore, immunohistochemical (IHC) was used to detect DNAJC1 expression in liver cancer tissues. Subsequently, the effect of DNAJC1 on the proliferation, migration, invasion and apoptosis of HCC cells was detected by knocking down DNAJC1. Finally, gene set enrichment analysis (GSEA) was used to investigate the potential mechanism of DNAJC1 and was verified by Western blotting. Results: DNAJC1 was highly expressed in HCC and was significantly associated with the prognosis of patients with HCC. Importantly, the proliferation, migration and invasion of Huh7 and MHCC97H cells were inhibited by the knockdown of DNAJC1 and the knockdown of DNAJC1 promoted Huh7 and MHCC97H cell apoptosis. Furthermore, compared to the negative control group, DNAJC1 knockdown in Huh7 and MHCC97H cells promoted the expression of p21, p53, p-p53(Ser20), Bax and E-cadherin proteins, while inhibiting the expression of PARP, MMP9, Vimentin, Snai1, Bcl-2 and N-cadherin proteins. Conclusions: DNAJC1 had a predictive value for the prognosis of HCC. Knockdown of DNAJC1 may inhibit HCC cell proliferation, migration and invasion and promote the HCC cell apoptosis through p53 and EMT signaling pathways.

Identification of possible sources for potentially toxic elements and polycyclic aromatic hydrocarbons and their spatially varying relationships in urban soils of Dublin, Ireland.

Potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs) harm the ecosystem and human health, especially in urban areas. Identifying and understanding their potential sources and underlying interactions in urban soils are critical for informed management and risk assessment. This study investigated the potential sources and the spatially varying relationships between 9 PTEs and PAHs in the topsoil of Dublin by combining positive matrix factorisation (PMF) and geographically weighted regression (GWR). The PMF model allocated four possible sources based on species concentrations and uncertainties. The factor profiles indicated the associations with high-temperature combustion (PAHs), natural lithologic factors (As, Cd, Co, Cr, Ni), mineralisation and mining (Zn), as well as anthropogenic inputs (Cu, Hg, Pb), respectively. In addition, selected representative elements Cr, Zn, and Pb showed distinct spatial interactions with PAHs in the GWR model. Negative relationships between PAHs and Cr were observed in all samples, suggesting the control of Cr concentrations by natural factors. Negative relationships between PAHs and Zn in the eastern and north-eastern regions were related to mineralisation and anthropogenic Zn-Pb mining. In contrast, the surrounding regions exhibited a natural relationship between these two variables with positive coefficients. Increasing positive coefficients from west to east were observed between PAHs and Pb in the study area. This special pattern was consistent with prevailing south-westerly wind direction in Dublin, highlighting the predominant influences on PAHs and Pb concentrations from vehicle and coal combustion through atmospheric deposition. Our results provided a better understanding of geochemical features for PTEs and PAHs in the topsoil of Dublin, demonstrating the efficiency of combined approaches of receptor models and spatial analysis in environmental studies.

New observation of perceptive mechanism behind the long-lasting change of people's community mobility: evidence from COVID-19 in China.

COVID-19 pandemic provides an opportunity to investigate how a new and long-lasting threat affects public risk perception and social distancing behavior, which is important for pandemic risk management and recovery of the tertiary industry. We have found that the mechanism that perception decides behavior changes over time. At the beginning of the pandemic, risk directly shapes people's willingness of going out. But under a persistent threat, perception no longer plays the direct role of shape people's willingness. Instead, perception indirectly influences the willingness by shaping people's judgment about the necessity of traveling. Switching from direct to indirect influence, perception's effect is enlarged, which partially prevents people from returning to normal life even if the governmental ban is removed in a zero-COVID community.

Identification of soil parent materials in naturally high background areas based on machine learning.

Recently, farmlands with high geological background of Cd derived from carbonate rock (CA) and black shale areas (BA) have received wide attention. However, although both CA and BA belong to high geological background areas, the mobility of soil Cd differs significantly between them. In addition to the difficulty in reaching the parent material in deep soil, it is challenging to perform land use planning in high geological background areas. This study attempts to determine the key soil geochemical parameters related to the spatial patterns of lithology and the main factors influencing the geochemical behavior of soil Cd, and ultimately uses them and machine-learning methods to identify CA and BA. In total, 10,814 and 4323 surface soil samples were collected from CA and BA, respectively. Hot spot analysis revealed that soil properties and soil Cd were significantly correlated with the underlying bedrock, except for TOC and S. Further research confirmed that the concentration and mobility of Cd in high geological background areas were mainly affected by pH and Mn. The soil parent materials were then predicted using artificial neural network (ANN), random forest (RF) and support vector machine (SVM) models. The ANN and RF models showed higher Kappa coefficients and overall accuracies than those of the SVM model, suggesting that ANNs and RF have the potential to predict soil parent materials from soil data, which might help in ensuring safe land use and coordinating activities in high geological background areas.

Identification of the spatial patterns and controlling factors of Se in soil and rice in Guangxi through hot spot analysis.

Selenium (Se) is essential to human health, anti-cancer, possessing antioxidant, and antiviral properties. In this study, the spatial patterns of rice Se and their varying relationship with soil Se on a regional scale were studied using hot spot analysis for the agricultural soils in Guangxi. According to the hot and cold spot maps, rice Se correlates positively with soil Se in Guangxi agricultural soils. High rice Se accompanies high soil Se in the central part of Guangxi (e.g., Liuzhou, Laibin), and low rice Se is in line with low soil Se in the western part (e.g., Baise). However, the hot spot analysis maps indicate that southwestern Guangxi exhibits a special characteristic of low rice Se with high soil Se (e.g., Chongzuo). This special pattern is strongly associated with the high concentrations of Fe2O3 (ferromanganese nodules) in the carbonate rock area. The hot spot analysis proves useful in revealing the spatial patterns of rice Se in Guangxi and identifying the hidden patterns.

Identification of high ecological risk areas with naturally high background value of soil Cd related to carbonate rocks.

The characteristics of high concentrations or high activity levels of heavy metals, especially Cd, in soils caused by the pedogenesis of rocks are attracting increased attention. Carbonate rocks and black shales often coexist during geological deposition, but the risk characteristics of heavy metals are different after their weathering into the soil. The purpose of this study was to investigate the element concentrations of a naturally high background value area, to identify patterns of different risk areas, and to make recommendations for the safe usage of farmland. The results showed that, compared with the soil in the carbonate rock area, the soil in the black shale area was more acidified and most of the heavy metal elements were leached. Based on the soil pH value and the heavy metal concentrations, an identification method for land risk areas within naturally high background values was established, and land planning was carried out using this method. The exceeding rates of Cd in rice for the preferential protection area and strict control area were 0.0 and 50.0%, respectively. Therefore, in naturally high background area, the identified lithology can apply to maximize the use of farmland resources. This method provides a basis for preliminary ecological risk screening in naturally high background value areas using the results of the soil survey. A suggestion for the prevention and control of soil pollution in areas with naturally high background values was put forward. In carbonate rock areas, the soil should be closely monitored to prevent soil acidification.

Development and applications of GIS-based spatial analysis in environmental geochemistry in the big data era.

The research of environmental geochemistry entered the big data era. Environmental big data is a kind of new method and thought, which brings both opportunities and challenges to GIS-based spatial analysis in geochemical studies. However, big data research in environmental geochemistry is still in its preliminary stage, and what practical problems can be solved still remain unclear. This short review paper briefly discusses the main problems and solutions of spatial analysis related to the big data in environmental geochemistry, with a focus on the development and applications of conventional GIS-based approaches as well as advanced spatial machine learning techniques. The topics discussed include probability distribution and data transformation, spatial structures and patterns, correlation and spatial relationships, data visualisation, spatial prediction, background and threshold, hot spots and spatial outliers as well as distinction of natural and anthropogenic factors. It is highlighted that the integration of spatial analysis on the GIS platform provides effective solutions to revealing the hidden spatial patterns and spatially varying relationships in environmental geochemistry, demonstrated by an example of cadmium concentrations in the topsoil of Northern Ireland through hot spot analysis. In the big data era, further studies should be more inclined to the integration and application of spatial machine learning techniques, as well as investigation on the temporal trends of environmental geochemical features.

Potential hot spots contaminated with exogenous, rare earth elements originating from e-waste dismantling and recycling.

Dismantling and recycling e-waste has been recognized as a potential emission source of rare earth elements (REEs). However, the presence of REEs in typical regional soils has yet to be studied. Given the potential health implications of such soil contamination, it is vital to study the characteristics, spatial distribution, and pollution level of REEs caused by e-waste dismantling as well as determine the influencing mechanism. This study focused on Guiyu Town as an example site, which is a typical e-waste dismantling base. From the site, 39 topsoil samples of different types were collected according to grid distribution points. Soil profiles were also collected in the dismantling and non-dismantling areas. The REE characteristic parameters showed that the REE distribution was abnormal and was affected by multiple factors. The results of the integrated pollution index showed that approximately 61.5% of soil samples were considered to be lightly polluted. Spatial distribution and correlation analysis showed that hot spots of REE-polluted soil coincided with known, main pollution sources. Moreover, there was a significant negative correlation (p ≤0.05) between the REE concentration and the distance from the pollution source. E-waste disassembly and recycling greatly affect the physical and chemical properties of the surrounding soil as well as downward migration areas. In the disassembly area, REE accumulated more easily in the surface layer (0-20 cm). Geographical detector results showed that distance factor was the main contribution factor for both light rare earth elements (LREE) and heavy rare earth element (HREE) (q = 34.59% and 53.33%, respectively). REE distribution in soil was nonlinear enhanced by different factors. Taken together, these results showed that e-waste disassembling and recycling not only directly affected the spatial distribution of REEs, but that their distribution was also affected by land use type and soil properties.

Selective and simultaneous high resolution 2-D imaging of AsIII, CrIII and SbIII and dissolved oxygen by developing a new DGT technique comprising a hybrid sensor.

A new diffusive gradients in thin films technique (HR-MPTS DGT) with mercapto-functionalized attapulgite in a binding gel was developed for simultaneous two-dimensional (2-D) chemical imaging of AsIII, CrIII and SbIII selectively at the submillimeter scale, combined with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis. The HR-MPTS DGT exhibited selective accumulation of AsIII, SbIII and CrIII (> 97%), yet negligible accumulation of AsV, SbV and CrVI (< 2%). Accumulation of AsIII, CrIII and SbIII on the binding gel had a linear relationship (R2 > 0.99) with the corresponding standardized laser ablation signals, proving the feasibility of LA-ICP-MS analysis. Analysis for AsIII, CrIII and SbIII was provided with favorable analytical precision (relative standard deviation <10%). With the purpose of evaluating the dynamics of AsIII, CrIII, SbIII and O2 in the rooting zone, a hybrid sensor, which comprises the HR-MPTS gel overlying an O2 planar optode, was deployed in rhizosphere sediments. Results showed that the consumption of both AsIII and SbIII due to the oxidation extended ~4.48 mm into the sediments, which was consistent with the extension length of the oxidized sediment layers around the roots created by O2 leakage.

Use of artificial neural network to evaluate cadmium contamination in farmland soils in a karst area with naturally high background values.

In recent years, the naturally high background value region of Cd derived from the weathering of carbonate has received wide attention. Due to the significant difference in soil Cd content and bioavailability among different parent materials, the previous land classification scheme based on total soil Cd content as the classification standard, has certain shortcomings. This study aims to explore the factors influencing soil Cd bioavailability in typical karst areas of Guilin and to suggest a scientific and effective farmland use management plan based on the prediction model. A total of 9393 and 8883 topsoil samples were collected from karst and non-karst areas, respectively. Meanwhile, 149 and 145 rice samples were collected together with rhizosphere soil in karst and non-karst areas, respectively. The results showed that the higher CaO level in the karst area was a key factor leading to elevated soil pH value. Although Cd was highly enriched in karst soils, the higher pH value and adsorption of Mn oxidation inhibited Cd mobility in soils. Conversely, the Cd content in non-karst soils was lower, whereas the Cd level in rice grains was higher. To select the optimal prediction model based on the correlation between Cd bioaccumulation factors and geochemical parameters of soil, artificial neural network (ANN) and linear regression prediction models were established in this study. The ANN prediction model was more accurate than the traditional linear regression model according to the evaluation parameters of the test set. Furthermore, a new land classification scheme based on an ANN prediction model and soil Cd concentration is proposed in this study, making full use of the spatial resources of farmland to ensure safe rice consumption.

Effect of biochar on transformation of dissolved organic matter and DTPA-extractable Cu and Cd during sediment composting.

This study investigated the influence of biochar on temperature, pH, organic matter (OM), seed germination index (GI), the fluorescent components of dissolved organic matter (DOM), and bioavailability of DTPA-extractable Cu and Cd during composting and analyzed the relation between DTPA-extractable metals with pH, OM, and the fluorescent components of DOM. Results showed that the addition of biochar shortened the thermophilic phase, reduced the pH at maturation period, accelerated the decomposition of OM, and raised GI. Besides, it promoted the formation of components with benzene ring in FA and HyI and the degradation of protein-like organic-matters in FA and HA, which was mainly related with the decrease of DTPA-extractable Cd and the increase of DTPA-extractable Cu. After composting, DTPA-extractable Cd in pile A and pile B were decreased by 37.15% and 27.54%, respectively, while the bioavailability of Cu in pile A and pile B was increased by 65.71% and 68.70%, respectively. All these findings demonstrate positive and negative impact produced by biochar into various heavy metals and the necessary of optimization measures with biochar in sediment composting.

Trends and influential factors of high ecological status mobility in Irish Rivers.

The decline in high ecological water status in rivers is a significant concern in European countries. It is thus important to investigate the factors that cause sites to lose high status in order to undertake measures to protect and restore high status water quality. Analysis of 20 years of water quality data reveals strong mobility between high status and non-high status (especially good status) rivers. Associations between this mobility and socio-economic and physical environmental variables were estimated by multinomial logistic regression at national scale and regional scale. Based on reported changes in water quality status cross across 1990, 2000 and 2010, four classes of the mobility of high status were defined in this study: those sites that maintain high status (maintain), enter high status (enter), fluctuate between high and non-high status (fluctuate) and exit from high status (exit). The national results indicate that agricultural activity as indicated by variables representing intensity of livestock farming (organic nitrogen) and tillage farming (cereal share) and elevation had significant negative impacts on high status rivers. Meanwhile, significant differences in population density and septic tank density between 'exit', 'maintain', 'fluctuate' and 'enter' classes indicate that these factors played important roles in the stability of high status rivers. The regional outcomes reveal differential significant pressures across regions. For example, rainfall and elevation had positive impacts on high status rivers in the north-west region, while organic nitrogen had a negative effect in the south-west. This paper demonstrates the challenge in achieving the Water Framework Directive goal of maintaining high status rivers, given the sensitive and highly differentiated nature of areas that have lost high status or fluctuated in and out of high status. This paper also suggests the necessity for localised policies and mitigation measures.

Carbonate bedrock control of soil Cd background in Southwestern China: Its extent and influencing factors based on spatial analysis.

Previous studies have found that Cadmium (Cd) may be condensed during the processes of the weathering and soil formation over carbonate bedrock, which is a typical phenomenon in the southwest region of China. However, the extent of the high value background and the geographical factors influencing its spatial distribution are still unknown. This study collected data from the Multi-Purpose Regional Geochemical Survey (MPRGS) and the Regional Geochemistry-National Reconnaissance Program (RGNR) to investigate the extent and its controlling factors based on spatial analysis. It was found that the RGNR is an ideal data source for regional Cd background studies. Spatially, the high Cd area (Cd > 1.5 m/kg with reference of the GB15618-2018 soil environmental quality in China, 68.9 × 103 km2) coincide well with the carbonate distribution. In the total area (68.9 × 103 km2) with high Cd concentration, 89.8% is related to carbonates. The composition of parent rock, climate conditions, and landuse are controlling factors of the enrichment. The high Cd background effect of limestone is higher than that of dolomite and their effects decease with increasing detritus component they contain. Warm and humid climate in forest land helps to enrich Cd during weathering. Soil Cd concentration related to carbonate background can be predicted by major element concentrations, which is useful for differentiating Cd background from human pollution in the future soil pollution monitoring. Modelling by artificial neural network (ANN) is recommended rather than tradition multiple linear methods (LM) as the latter may have the effect of collinearity.

Influences of geological factors on the distribution of uranium in drinking water limescale in the junction zone of the East European Platform and the Southern Urals.

An assessment of uranium contents and distribution in drinking water limescale has been conducted in the Republic of Bashkortostan (RB), Russia. A total of 515 limescale samples from 262 settlements of the RB were analyzed. The spread of U concentration values in limescale samples ranged from 0.01 to 61.0 µg/g. Elevated U concentrations in the West of the RB corresponded with the horsts of the granite-gneiss crystalline basement of the South-Tatar Dome and their Eastern slopes, the areas with the Lower Permian red beds and the oil and gas fields. The U migration from the granite-gneiss basement is attributed to the tectonic factor and hydrocarbons movement. Elevated concentrations of U within the South of the RB are associated primarily with the deposits of the Southern Ural brown coal basin. The Bashkir Trans-Urals anomalies are mainly associated with Lower Paleozoic eclogite complex, Devonian and Carboniferous volcanic-sedimentary, carbonate, intrusive formations, as well as the Jurassic cover of terrigenous marine sediments. The negative anomalies of the spatial distribution of U are located in the area of the Ufimian Plateau mainly composed of limestone.