549 research outputs found
Research on Large-scale Energy Storage of Chinese Power System Based on Demand Analysis
With the construction and development of a low carbon and environmental protection society, China is promoting the construction of a clean, low carbon, safe and efficient energy supply system, the most critical of which is to promote the rapid construction of new energy installed capacity. However, with the continuous expansion of the new energy installed capacity, the random volatility of the power supply has become an important factor that puzzles the power balance of the current power system, not only formed a larger peak pressure, but also became one of the important factors restricting the development of new energy. At the same time, the new energy power electronic equipment has weak supporting characteristics, which also makes the proportion of new energy power system continues to increase, and has a high impact on security. In this context, this paper carries out a demand analysis, firstly discussing the demand for large-scale energy storage in the development of new energy for power system, and secondly analyzing the demand for large-scale energy storage in the safe operation of large power grid, so as to promote the construction of GW-level electrochemical energy storage power station and effectively deal with the power imbalance and safety problems
Transplantation of Bone Marrow Mesenchymal Stem Cells Prevents Radiation-Induced Artery Injury by Suppressing Oxidative Stress and Inflammation
The present study aims to explore the protective effect of human bone marrow mesenchymal stem cells (hBMSCs) on radiation-induced aortic injury (RIAI). hBMSCs were isolated and cultured from human bone marrow. Male C57/BL mice were irradiated with a dose of 18-Gy 6MV X-ray and randomly treated with either vehicle or hBMSCs through tail vein injection with a dose of 103 or 104 cells/g of body weight (low or high dose of hBMSCs) within 24 h. Aortic inflammation, oxidative stress, and vascular remodeling were assessed by immunohistochemical staining at 3, 7, 14, 28, and 84 days after irradiation. The results revealed irradiation caused aortic cell apoptosis and fibrotic remodeling indicated by aortic thickening, collagen accumulation, and increased expression of profibrotic cytokines (CTGF and TGF-β). Further investigation showed that irradiation resulted in elevated expression of inflammation-related molecules (TNF-α and ICAM-1) and oxidative stress indicators (4-HNE and 3-NT). Both of the low and high doses of hBMSCs alleviated the above irradiation-induced pathological changes and elevated the antioxidant enzyme expression of HO-1 and catalase in the aorta. The high dose even showed a better protective effect. In conclusion, hBMSCs provide significant protection against RIAI possibly through inhibition of aortic oxidative stress and inflammation. Therefore, hBMSCs can be used as a potential therapy to treat RIAI
Liraglutide attenuates high glucose-induced abnormal cell migration, proliferation, and apoptosis of vascular smooth muscle cells by activating the GLP-1 receptor, and inhibiting ERK1/2 and PI3K/Akt signaling pathways
A stream processing framework based on linked data for information collaborating of regional energy networks
© 2005-2012 IEEE. Coordinating of energy networks to form a city-level multidimensional integrated energy system becomes a new trend in Energy Internet (EI). The collaborating in the information layer is a core issue to achieve smart integration. However, the heterogeneity of multiagent data, the volatility of components, and the real-time analysis requirement in EI bring significant challenges. To solve these problems, in this article we propose a stream processing framework based on linked data for information collaboration among multiple energy networks. The framework provides a universal data representation based on linked data and semantic relation discovery approach to model and semantically fuse heterogeneous data. Semantics-based information transmission contracts and channels are automatically generated to adapt to structural changes in EI. A multimodel-based dynamic adjusting stream processing is implemented using data semantics. A real-world case study is implemented to demonstrate the adaptability, feasibility, and flexibility of the proposed framework
The anti-tumor histone deacetylase inhibitor SAHA and the natural flavonoid curcumin exhibit synergistic neuroprotection against amyloid-beta toxicity
With the trend of an increasing aged population worldwide, Alzheimer’s disease (AD), an age-related neurodegenerative disorder, as one of the major causes of dementia in elderly people is of growing concern. Despite the many hard efforts attempted during the past several decades in trying to elucidate the pathological mechanisms underlying AD and putting forward potential therapeutic strategies, there is still a lack of effective treatments for AD. The efficacy of many potential therapeutic drugs for AD is of main concern in clinical practice. For example, large bodies of evidence show that the antitumor histone deacetylase (HDAC) inhibitor, suberoylanilidehydroxamic acid (SAHA), may be of benefit for the treatment of AD; however, its extensive inhibition of HDACs makes it a poor therapeutic. Moreover, the natural flavonoid, curcumin, may also have a potential therapeutic benefit against AD; however, it is plagued by low bioavailability. Therefore, the integrative effects of SAHA and curcumin were investigated as a protection against amyloid-beta neurotoxicity in vitro. We hypothesized that at low doses their synergistic effect would improve therapeutic selectivity, based on experiments that showed that at low concentrations SAHA and curcumin could provide comprehensive protection against Ab25–35-induced neuronal damage in PC12 cells, strongly implying potent synergism. Furthermore, network analysis suggested that the possible mechanism underlying their synergistic action might be derived from restoration of the damaged functional link between Akt and the CBP/p300 pathway, which plays a crucial role in the pathological development of AD. Thus, our findings provided a feasible avenue for the application of a synergistic drug combination, SAHA and curcumin, in the treatment of AD
Molecular Determinants of Magnolol Targeting Both RXRα and PPARγ
Nuclear receptors retinoic X receptor α (RXRα) and peroxisome proliferator activated receptor γ (PPARγ) function potently in metabolic diseases, and are both important targets for anti-diabetic drugs. Coactivation of RXRα and PPARγ is believed to synergize their effects on glucose and lipid metabolism. Here we identify the natural product magnolol as a dual agonist targeting both RXRα and PPARγ. Magnolol was previously reported to enhance adipocyte differentiation and glucose uptake, ameliorate blood glucose level and prevent development of diabetic nephropathy. Although magnolol can bind and activate both of these two nuclear receptors, the transactivation assays indicate that magnolol exhibits biased agonism on the transcription of PPAR-response element (PPRE) mediated by RXRα:PPARγ heterodimer, instead of RXR-response element (RXRE) mediated by RXRα:RXRα homodimer. To further elucidate the molecular basis for magnolol agonism, we determine both the co-crystal structures of RXRα and PPARγ ligand-binding domains (LBDs) with magnolol. Structural analyses reveal that magnolol adopts its two 5-allyl-2-hydroxyphenyl moieties occupying the acidic and hydrophobic cavities of RXRα L-shaped ligand-binding pocket, respectively. While, two magnolol molecules cooperatively accommodate into PPARγ Y-shaped ligand-binding pocket. Based on these two complex structures, the key interactions for magnolol activating RXRα and PPARγ are determined. As the first report on the dual agonist targeting RXRα and PPARγ with receptor-ligand complex structures, our results are thus expected to help inspect the potential pharmacological mechanism for magnolol functions, and supply useful hits for nuclear receptor multi-target ligand design
Particle sizing in concentrated suspensions by use of steady-state, continuous-wave photon-migration techniques
We demonstrate a new approach for determining particle-size distribution in concentrated suspensions from spectral measurement of isotropic scattering coefficients by use of steady-state, continuous-wave photon-migration techniques. Successful recovery of particle-size distribution for TiO_2 suspensions in the form of log-normal functions is achieved through a regularized inverse algorithm, into which a synthesized scheme of Marquardt and Tikhonov regularizations has been incorporated. Our results for dense TiO_2 suspensions with three different particle concentrations are in excellent agreement with the size distribution as measured with x-ray sedimentation
Aerosol-Assisted Synthesis of Monodisperse Single-Crystalline α-Cristobalite Nanospheres
Monodisperse single-crystalline α-cristobalite nanospheres have been synthesized by hydrocarbon-pyrolysis-induced carbon deposition on amorphous silica aerosol nanoparticles, devitrification of the coated silica at high temperature, and subsequent carbon removal by oxidation. The nanosphere size can be well controlled by tuning the size of the colloidal silica precursor. Uniform, high-purity nanocrystalline α-cristobalite is important for catalysis, nanocomposites, advanced polishing, and understanding silica nanotoxicology
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