Improving Joint Operation System of Reservoir Groups in the Yangtze River Basin: A Legal Discussion

As China’s largest river basin, the Yangtze River Basin has the most mega reservoir groups worldwide. To protect the entire basin, the Central Government developed a system of joint operations of key reservoir groups in the Yangtze River Basin. This paper examines this joint operation system from a legal perspective and discusses its implementation as well as the challenges in practice. The following issues impede the effective implementation of the joint operation system: a lacking legal basis for the system, limitations related to the organizations that participate in the joint operations, limitations on the scope and objects of the joint operation system, and a lacking systematic structure for operation. This paper offers suggestions to improve the system

Application of dispersive liquid–liquid microextraction and reversed phase-high performance liquid chromatography for the determination of two fungicides in environmental water samples

Dispersive liquid–liquid microextraction (DLLME) has been developed for the extraction and preconcentration of diethofencarb (DF) and pyrimethanil (PM) in environmental water. In the method, a suitable mixture of extraction solvent (50 μL carbon tetrachloride) and dispersive solvent (0.75 mL acetonitrile) are injected into the aqueous samples (5.00 mL) and the cloudy solution is observed. After centrifugation, the enriched analytes in the sediment phase were determined by HPLC-VWD. Different influencing factors, such as the kind and volume of extraction and dispersive solvent, extraction time and salt effect were investigated. Under the optimum conditions, the enrichment factors for DF and PM were both 108 and the limit of detection were 0.021 ng mL−1 and 0.015 ng mL−1, respectively. The linear ranges were 0.08–400 ng mL−1 for DF and 0.04–200 ng mL−1 for PM. The relative standard deviation (RSDs) were both almost at 6.0% (n = 6). The relative recoveries from samples of environmental water were from the range of 87.0 to 107.2%. Compared with other methods, DLLME is a very simple, rapid, sensitive (low limit of detection) and economical (only 5 mL volume of sample) method

Di-μ-benzoato-κ3 O,O′:O;κ3 O:O,O′-bis­[aqua­(nitrato-κO)(1,10-phenanthroline-κ2 N,N′)lead(II)]

The title compound, [Pb2(C7H5O2)2(NO3)2(C12H8N2)2(H2O)2], crystallizes as a dinuclear centrosymmetric dimer containing two PbII atoms bridged by two benzoate ligands. Each PbII atom is seven-coordinated by a water mol­ecule, a nitrate anion, a 1,10-phenanthroline (phen) ligand and two benzoate anions. The crystal packing is stabilized by O—H⋯O hydrogen bonds and by π–π stacking between neighboring phen ligands, with a centroid–centroid distance of 3.557 (3) Å

A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy

OBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis

Global Positive Periodic Solutions of Generalized n

We consider the following generalized n-species Lotka-Volterra type and Gilpin-Ayala type competition systems with multiple delays and impulses: xi′(t)=xi(t)[ai(t)-bi(t)xi(t)-∑j=1n‍cij(t)xjαij(t-ρij(t))-∑j=1n‍dij(t)xjβij(t-τij(t))-∑j=1n‍eij(t)∫-ηij0‍kij(s)xjγij(t+s)ds-∑j=1n‍fij(t)∫-θij0‍Kij(ξ)xiδij(t+ξ)xjσij(t+ξ)dξ],a.e, t>0, t≠tk; xi(tk+)-xi(tk-)=hikxi(tk), i=1,2,…,n, k∈Z+. By applying the Krasnoselskii fixed-point theorem in a cone of Banach space, we derive some verifiable necessary and sufficient conditions for the existence of positive periodic solutions of the previously mentioned. As applications, some special cases of the previous system are examined and some earlier results are extended and improved

Assessing the soundness of water governance: lessons learned from applying the 10 Building Blocks Approach

Sound governance is needed to address water issues, but soundness is a contested concept that should be further specified in societal debates. These debates can benefit from interdisciplinary knowledge. The 10 Building Blocks Approach, a tool developed to generate such knowledge, has been widely applied in research and teaching. In this paper, we draw on the literature and reflect on the experiences of using this approach by elucidating the strengths and weaknesses identified during its applications. Based on our reflections, we propose a revised version of the approach

Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis

Background Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. Methods The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria│log2 fold change (logFC)|>1.0 and p 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. Results Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. Conclusion The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC