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Groundwater is susceptible to arsenic contamination by sediment with high arsenic content, which is the primary culprit of regional arsenic pollution and poisoning. To explore the influence of the change in hydrodynamic conditions caused by changes in the sedimentary environment over time on arsenic content in sediments during the Quaternary, the hydrodynamic characteristics and arsenic content enrichment of borehole sediments were studied in typical high-arsenic groundwater areas of the Jianghan–Dongting Basin, China. The regional hydrodynamic conditions represented by each borehole location were analyzed, the correlation between the variation in groundwater dynamics characteristics and arsenic content in different hydrodynamic periods was analyzed, and the relationship between arsenic content and grain size distribution was quantitatively investigated using grain size parameter calculation, elemental analysis, and statistical estimates of arsenic content in borehole sediments. We observed that the relationship between arsenic content and hydrodynamic conditions differed between sedimentary periods. Furthermore, arsenic content in the sediments from the borehole at Xinfei Village was significantly and positively correlated with a grain size of 127.0–240.0 μm. For the borehole at Wuai Village, arsenic content was significantly and positively correlated with a grain size of 1.38–9.82 μm size (at 0.05 level of significance). However, arsenic content was inversely correlated with grain sizes of 110.99–716.87 and 133.75–282.07 μm at p values of 0.05 and 0.01, respectively. For the borehole at Fuxing Water Works, arsenic content was significantly and positively correlated with a grain size of 409.6–655.0 μm size (at 0.05 level of significance). Arsenic tended to be enriched in transitional and turbidity facies sediments with normal corresponding hydrodynamic strength but poor sorting. Furthermore, continuous and stable sedimentary sequences were conducive to arsenic enrichment. Fine-grain sediments provided abundant potential adsorption sites for high-arsenic sediments, but finer particle size was not correlated with higher arsenic levels. [ABSTRACT FROM AUTHOR]

Purpose: The poor outcomes in glioblastoma necessitate new therapeutic target. Isoprenylcysteine carboxyl methyltransferase (ICMT), a unique enzyme of the final step of prenylation that modifies activities of oncogenic proteins, represents a promising target for many cancers. Methods: Expression pattern, function and downstream pathway of ICMT in glioblastoma were analyzed using immunohistochemistry, ELISA, cellular assays and immunoblotting method. Combinatory effect was analyzed using Chou-Talalay approach. Results: Upregulation of ICMT expression is a common phenomenon in glioblastoma patients regardless of clinicopathological characteristics. Gain-of-function and loss-of-function analysis support the role of ICMT in glioblastoma growth and survival but not migration. Importantly, pharmacological inhibitors of ICMT are effectively against glioblastoma cells while sparing normal neuron cells, and furthermore that they act synergistically with chemotherapeutic drugs. Consistently, ICMT inhibitor UCM-1336 significantly inhibits glioblastoma growth without causing toxicity in mice. Mechanistic studies demonstrate that Ras/Raf/Mek/Erk rather than Ras/PI3K/Akt/mTOR is the downstream pathway of ICMT-mediated glioblastoma growth. Conclusions: Our findings provide the proof-of-concept of pharmacologically targeting ICMT in the treatment of glioblastoma via deactivation of Ras/Raf/Mek/Erk. [ABSTRACT FROM AUTHOR]

Inflammatory processes have long been implicated in the development of delayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH). Macrophage migration inhibitory factor (MIF) has been implicated in inflammation. The aim of this study was to assess whether serum levels of MIF at admission helps to predict which patients with aSAH would subsequently develop DCI. All patients with first-ever aSAH admitted between 2016 and 2017 were considered for inclusion in this prospective study. Primary study outcome was development of DCI at discharge. Serum levels of MIF, C-reactive protein (CRP), and interleukin-6 (IL-6) were tested at admission. The relation of serum levels of MIF at admission with DCI was assessed by the logistic regression models. In this study, 201 patients were included. A correlation between Hunt and Hess score and serum levels of MIF was found (r = 0.340; P < 0.001). Fifty-two of the 201 aSAH (25.9%) were defined as DCI, and the obtained MIF level in those patients was higher than in those patients without DCI [26.4 (IQR, 22.6–32.4) ng/ml vs. 20.4 (16.4–24.6) ng/ml; P < 0.001). As a continuous variable, MIF was associated with the risk of DCI. When serum level of MIF was elevated by each 1 ng/ml, the unadjusted risk of DCI was increased by 18% (OR = 1.18 [1.12–1.25], P < 0.001), while the adjusted risk was increased by 10% (1.10 [1.03–1.19], P = 0.001). With the area under the curve (AUC) of 0.780 (95% CI, 0.710–0.849), the MIF showed a great discriminatory ability for DCI than CRP (0.665, 0.582–0.748; P < 0.001) and IL-6 (0.721, 0.642–0.799; P = 0.001). Interestingly, the combined model (MIF/IL-6/CRP) improved the MIF to predict DCI (AUC of the combined model: 0.811; 95% CI, 0.751–0.871; P = 0.024). Furthermore, inclusion of MIF in the existing risk factors for the prediction of DCI enhanced the index and net reclassification improvement (NRI) (P < 0.001) and integrated discrimination improvement (IDI) (P = 0.005) values, confirming the effective reclassification and discrimination. The data showed that elevated MIF serum level accurately identifies patients at highest risk for developing DCI following aSAH. [ABSTRACT FROM AUTHOR]

Untreated disposal of wastewater from coal-fired power plants has environmental and public health concerns in the developing Shanbei Energy Base, Northwest China. An in situ experiment was conducted in the easily accessible wind-blown sands to study their efficiency in removal of pollutants. Approximately 245 l of wastewater was used in the test, which lasted 409 min. Sand samples were collected at 5 discrete depths, 0.2, 0.4, 0.6, 1, and 1.5 m from the surface before, at the end of, and 20 days after the infiltration test. Pollutants commonly found in wastewater were analyzed for all the sand samples. 20 days after infiltration, the content of As in the sand samples had a general reduction, decreased from original 0.0109-0.0132 to 0.005 mg/kg. The content of N-NH also decreased from original 1.1-1.5 to 0.8-1.0 mg/kg. But the content of Cd and petroleum was stable and had no decreasing trend. The test indicates the wind-blown sands are more effective for As and N-NH, but less effective for petroleum and Cd. [ABSTRACT FROM AUTHOR]

This study investigated groundwater contamination in the Yuxi River Valley in northern Shaanxi Province, one of largest energy resource centers in China. Groundwater samples collected from 129 locations in the Yuxi River Valley area were analyzed and evaluated to establish the local groundwater quality zonings. Results indicate that groundwater in the Yuxi River Valley is contaminated, and the dominant contaminants in the groundwater are ammonium (NH4 +) and nitrite (NO2 −). Maximal concentration of NH4 + was detected at 0.019 and 3.50 mg/L in the samples collected up-gradient and down-gradient, respectively, of the segment of Yuxi River that flows through Yulin City. Concentration of NO2 − was detected at 0.0015 and 1.522 mg/L, respectively from the same samples. Zones I through IV, from non-polluted to seriously polluted, were identified for groundwater quality in the Yuxi River Valley. We attribute the groundwater contamination in the Yuxi River valley to sources in the Yulin township, presumably its wastewater discharge. [ABSTRACT FROM AUTHOR]

Feicheng Basin is an important energy base in Shandong Province, China. The Ordovician limestone is the main aquifer for water supply in the basin. As a result of the current practice in which individual water users control the exploitation of the karst water, the regional groundwater level has dropped more than 30 m over the last 20 years. The groundwater is overdrawn in approximately 300 km2 because of the poor management from 1981. A numerical model with distributed parameters is developed for the karst aquifer to help properly manage the water resource and sustain its utilization. The responding matrix method is used to couple the prediction model and the management model. The objective of the modeling exercises is to obtain the maximum amount of water while keeping the water level drawdown within an acceptable level. The optimum management scheme is selected among two proposed designs. The recommended measures from this study include (1) improvement of water use efficiency in industries, (2) comprehensive utilization of the water pumped from the mines, and (3) improvement of the irrigation practice. When the domestic water supply and corporates water demand take the top priorities, the numerical modeling provides a useful tool to help with the rational distribution of the karst water resources among different water users. [ABSTRACT FROM AUTHOR]

Experimentally-determined or computationally-predicted protein phosphorylation sites for distinctive species are becoming increasingly common. In this paper, we compare the predictive performance of a novel classification algorithm with different encoding schemes to develop a rice-specific protein phosphorylation site predictor. Our results imply that the combination of Amino acid occurrence Frequency with Composition of K-Spaced Amino Acid Pairs (AF-CKSAAP) provides the best description of relevant sequence features that surround a phosphorylation site. A support vector machine (SVM) using AF-CKSAAP achieves the best performance in classifying rice protein phophorylation sites when compared to the other algorithms. We have used SVM with AF-CKSAAP to construct a rice-specific protein phosphorylation sites predictor, Rice_Phospho 1.0 (http://bioinformatics.fafu.edu.cn/rice_phospho1.0). We measure the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) of Rice_Phospho 1.0 to be 82.0% and 0.64, significantly higher than those measures for other predictors such as Scansite, Musite, PlantPhos and PhosphoRice. Rice_Phospho 1.0 also successfully predicted the experimentally identified phosphorylation sites in LOC_Os03g51600.1, a protein sequence which did not appear in the training dataset. In summary, Rice_phospho 1.0 outputs reliable predictions of protein phosphorylation sites in rice, and will serve as a useful tool to the community. [ABSTRACT FROM AUTHOR]