37 research outputs found
Krylov implicit integration factor discontinuous Galerkin methods on sparse grids for high dimensional reaction-diffusion equations
Computational costs of numerically solving multidimensional partial
differential equations (PDEs) increase significantly when the spatial
dimensions of the PDEs are high, due to large number of spatial grid points.
For multidimensional reaction-diffusion equations, stiffness of the system
provides additional challenges for achieving efficient numerical simulations.
In this paper, we propose a class of Krylov implicit integration factor (IIF)
discontinuous Galerkin (DG) methods on sparse grids to solve reaction-diffusion
equations on high spatial dimensions. The key ingredient of spatial DG
discretization is the multiwavelet bases on nested sparse grids, which can
significantly reduce the numbers of degrees of freedom. To deal with the
stiffness of the DG spatial operator in discretizing reaction-diffusion
equations, we apply the efficient IIF time discretization methods, which are a
class of exponential integrators. Krylov subspace approximations are used to
evaluate the large size matrix exponentials resulting from IIF schemes for
solving PDEs on high spatial dimensions. Stability and error analysis for the
semi-discrete scheme are performed. Numerical examples of both scalar equations
and systems in two and three spatial dimensions are provided to demonstrate the
accuracy and efficiency of the methods. The stiffness of the reaction-diffusion
equations is resolved well and large time step size computations are obtained
Different Origins of the Fractionation of Platinum-Group Elements in Raobazhai and Bixiling Mafic-Ultramafic Rocks from the Dabie Orogen, Central China
Exploration of the hypoglycemic mechanism of Fuzhuan brick tea based on integrating global metabolomics and network pharmacology analysis
Introduction: Fuzhuan brick tea (FBT) is a worldwide popular beverage which has the appreciable potential in regulating glycometabolism. However, the reports on the hypoglycemic mechanism of FBT remain limited.Methods: In this study, the hypoglycemic effect of FBT was evaluated in a pharmacological experiment based on Kunming mice. Global metabolomics and network pharmacology were combined to discover the potential target metabolites and genes. In addition, the real-time quantitative polymerase chain reaction (RT-qPCR) analysis was performed for verification.Results: Seven potential target metabolites and six potential target genes were screened using the integrated approach. After RT-qPCR analysis, it was found that the mRNA expression of VEGFA, KDR, MAPK14, and PPARA showed significant differences between normal and diabetes mellitus mice, with a retracement after FBT treatment.Conclusion: These results indicated that the hypoglycemic effect of FBT was associated with its anti-inflammatory activities and regulation of lipid metabolism disorders. The exploration of the hypoglycemic mechanism of FBT would be meaningful for its further application and development
The Antimicrobial Peptide Mastoparan X Protects Against Enterohemorrhagic Escherichia coli O157:H7 Infection, Inhibits Inflammation, and Enhances the Intestinal Epithelial Barrier
Escherichia coli can cause intestinal diseases in humans and livestock, destroy the intestinal barrier, exacerbate systemic inflammation, and seriously threaten human health and animal husbandry development. The aim of this study was to investigate whether the antimicrobial peptide mastoparan X (MPX) was effective against E. coli infection. BALB/c mice infected with E. coli by intraperitoneal injection, which represents a sepsis model. In this study, MPX exhibited no toxicity in IPEC-J2 cells and notably suppressed the levels of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), myeloperoxidase (MPO), and lactate dehydrogenase (LDH) released by E. coli. In addition, MPX improved the expression of ZO-1, occludin, and claudin and enhanced the wound healing of IPEC-J2 cells. The therapeutic effect of MPX was evaluated in a murine model, revealing that it protected mice from lethal E. coli infection. Furthermore, MPX increased the length of villi and reduced the infiltration of inflammatory cells into the jejunum. SEM and TEM analyses showed that MPX effectively ameliorated the jejunum damage caused by E. coli and increased the number and length of microvilli. In addition, MPX decreased the expression of IL-2, IL-6, TNF-α, p-p38, and p-p65 in the jejunum and colon. Moreover, MPX increased the expression of ZO-1, occludin, and MUC2 in the jejunum and colon, improved the function of the intestinal barrier, and promoted the absorption of nutrients. This study suggests that MPX is an effective therapeutic agent for E. coli infection and other intestinal diseases, laying the foundation for the development of new drugs for bacterial infections
Distribution and Source Apportionment of Heavy Metals in Soil around Dexing Copper Mine in Jiangxi Province, China
The soil heavy metal pollution around the mine threatens crop growth and human health. Intensively studies of the distribution characteristics and source of soil heavy metals around some typical mines are very crucial for environmental management and green development of mine. A total of eighty-nine soil samples, twenty-one sediment samples, five waste rock samples and two tailing sand samples were sampled to investigate copper (Cu), lead (Pb), zinc (Zn), arsenic (As), cadmium (Cd), chromium (Cr) and mercury (Hg) in soil, sediment, waste rocks and tailings sand around Dexing Copper Mine, Jiangxi Province, China. The concentrations of the seven heavy metals were determined using inductively coupled plasma mass spectrometry ICP-MS/atomic fluorescence spectroscopy (AFS). The Igeo values of soil heavy metal showed that 100% of Cu were at an unpolluted-to-moderately-polluted level (Igeo > 0), more than 50% of Cu were heavily polluted (Igeo > 3), 65.16%, and 22.47%, 7.86% and 7.87% of the soil samples for Cd, Hg, As and Zn were overly moderately polluted (Igeo > 1). A total of 13.48% and 11.24% of the soil samples for Pb and Cr, respectively, were moderately polluted (1 geo and RSVCAL, the soils around Dexing Copper Mine were polluted by heavy metals to some extent, with especially the Cu pollution of soil being the most serious. These heavy metal concentrations exceeding RSVCAL have threatened the safety of agricultural products. The results of soil profile analysis, principal component analysis (PCA) and cluster analysis (CA) indicated that the mining activities of Dexing copper mine should be the main source of Cu in the soil. High As concentration in soil obviously caused by the copper mine as well. In addition, Dexing Copper Mine should partly account for soil pollution by Zn, Pb, Cd, Hg and Cr around the mine
Quantifying Impacts of Land-Use/Cover Change on Urban Vegetation Gross Primary Production: A Case Study of Wuhan, China
This study quantified the impacts of land-use/cover change (LUCC) on gross primary production (GPP) during 2000–2013 in a typical densely urbanized Chinese city, Wuhan. GPP was estimated at 30-m spatial resolution using annual land cover maps, meteorological data of the baseline year, and the normalized difference vegetation index (NDVI), which was generated with the spatial and temporal adaptive reflectance fusion model (STARFM) based on Landsat and MODIS images. The results showed that approximately 309.95 Gg C was lost over 13 years, which was mainly due to the conversion from cropland to built-up areas. The interannual variation of GPP was affected by the change of vegetation composition, especially the increasing relative fraction of forests. The loss of GPP due to the conversion from forest to cropland fluctuated through the study period, but showed a sharp decrease in 2007 and 2008. The gain of GPP due to the conversion from cropland to forest was low between 2001 and 2009, but increased dramatically between 2009 and 2013. The change rate map showed an increasing trend along the highways, and a decreasing trend around the metropolitan area and lakes. The results indicated that carbon consequences should be considered before land management policies are put forth
Research Progress of Electrolytic Aluminum Overhaul Slag Disposal
As the main solid waste of the electrolytic aluminum industry, overhaul slag contains a large amount of hazardous substances, and how to treat it harmlessly and efficiently recover the valuable substances in it has become an urgent problem in the aluminum industry in recent years. This article analyzes and summarizes the composition and hazards of the overhaul slag and the current development status of domestic and international electrolytic aluminum overhaul slag disposal, and points out the development direction of hazardous waste disposal in China's electrolytic aluminum industry
Quantifying Impacts of Land-Use/Cover Change on Urban Vegetation Gross Primary Production: A Case Study of Wuhan, China
Yishen-tongbi decoction inhibits excessive activation of B cells by activating the FcγRIIb/Lyn/SHP-1 pathway and attenuates the inflammatory response in CIA rats
Rheumatoid arthritis (RA) is a chronic autoimmune disease. Strong evidence supports that excessive activation of B cells plays a critical role in the pathogenesis of RA. Fc gamma receptor b (FcγRIIb) is the B cell inhibitory receptor and inhibits BCR (B cell receptor) signalling in part by selectively dephosphorylating CD19 which is considered a co-receptor for BCR and is essential for B cell activation. Our previous study demonstrated that a FcγRIIb I232T polymorphism presented a strong genetic link to RA and may lead to the excessive activation of B cells. Therefore, novel therapeutic strategies and drugs that can effectively inhibit the excessive activation of B cells by regulating the FcγRIIb are necessary for the treatment of RA. Therefore, we used Burkitt’s lymphoma ST486 human B cells (lacking endogenous FcγRIIb) transfected with the 232Thr loss-of-function mutant to construct a FcγRIIb mutant cell line (ST486), and we demonstrated that YSTB treatment not only reduced proliferation and promoted apoptosis in ST486 cells but also did so in a dose-dependent manner. Furthermore, the intracellular Ca2+ flux of ST486 cells was decreased after treatment with YSTB, inhibiting the excessive activation of ST486 cells, and these effects correlated with the CD19/FcγRIIb-Lyn-SHP-1 pathways. Our data showed that YSTB treatment inhibited the expression of phosphorylated CD19 and upregulated the protein expression of FcγRIIb, Lyn, and SHP-1. Additionally, the CIA model was established to explore the anti-inflammatory and inhibitory effects of YSTB on bone destruction, and we found that YSTB decreased the paw oedema and arthritis index (AI) in CIA rats. It is worth mentioning that YSTB clearly decreased the AI earlier than methotrexate (MTX) (day 10 vs 16). Moreover, synovial hyperplasia, inflammatory cell infiltration and cartilage surface erosion in CIA rats were noticeably reduced after treatment with YSTB as evidenced by histopathological examination. Finally, we found that YSTB treatment suppressed bone erosion and joint space score (JNS) in CIA rats as evidenced by radiographic assessment. In summary, these data suggest that YSTB has great therapeutic potential for RA treatment
Exploring the Role of the Spatial Characteristics of Visible and Near-Infrared Reflectance in Predicting Soil Organic Carbon Density
Soil organic carbon stock plays a key role in the global carbon cycle and the precision agriculture. Visible and near-infrared reflectance spectroscopy (VNIRS) can directly reflect the internal physical construction and chemical substances of soil. The partial least squares regression (PLSR) is a classical and highly commonly used model in constructing soil spectral models and predicting soil properties. Nevertheless, using PLSR alone may not consider soil as characterized by strong spatial heterogeneity and dependence. However, considering the spatial characteristics of soil can offer valuable spatial information to guarantee the prediction accuracy of soil spectral models. Thus, this study aims to construct a rapid and accurate soil spectral model in predicting soil organic carbon density (SOCD) with the aid of the spatial autocorrelation of soil spectral reflectance. A total of 231 topsoil samples (0–30 cm) were collected from the Jianghan Plain, Wuhan, China. The spectral reflectance (350–2500 nm) was used as auxiliary variable. A geographically-weighted regression (GWR) model was used to evaluate the potential improvement of SOCD prediction when the spatial information of the spectral features was considered. Results showed that: (1) The principal components extracted from PLSR have a strong relationship with the regression coefficients at the average sampling distance (300 m) based on the Moran’s I values. (2) The eigenvectors of the principal components exhibited strong relationships with the absorption spectral features, and the regression coefficients of GWR varied with the geographical locations. (3) GWR displayed a higher accuracy than that of PLSR in predicting the SOCD by VNIRS. This study aimed to help people realize the importance of the spatial characteristics of soil properties and their spectra. This work also introduced guidelines for the application of GWR in predicting soil properties by VNIRS