Study on the bioactive ingredients and mechanism of Huangqi against diabetic retinopathy based on network pharmacology and experimental verification.

BACKGROUND: Diabetic retinopathy (DR) is one of the most well-known microvascular complications of diabetes mellitus. As a traditional Chinese medicine, Huangqi (HQ), has been used for treating DR for a long time. However, its anti-DR active ingredients and mechanism are still unknown. Therefore, we designed this study to explore the active components and mechanism of HQ against DR via network pharmacology analysis. METHODS: The ingredients of HQ, potential targets of HQ and DR were obtained from public databases. We employed the protein-protein interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis to identify core targets and pathways of HQ against DR. Finally, molecular docking and vitro experiments were applied to validate our results. RESULTS: A total of 34 potential targets of HQ against DR were obtained. Based on PPI network, VEGFA, PTGS2, IL6 and CCL2 were considered as core targets. GO analysis involved 692 biological processes, 21 cellular components and 35 molecular functions. KEGG enrichment analysis manifested that the anti-DR effect of HQ was mainly mediated via the AGE-RAGE signaling pathway in diabetic complications. The molecular docking results indicated that kaempferol had higher affinity with CCL2, IL-6, VEGFA and PTGS2. The vitro experiments showed that the mRNA expressions of CCL2, IL-6, VEGFA and PTGS2 in ARPE-19 cell were differentially decreased after kaempferol treatment. CONCLUSION: This study preliminarily unveiled that the therapeutic efficacy of HQ against DR might be attributed to the reduced expression of CCL2, IL-6, VEGFA and PTGS2.

A highly robust cluster-based indium(III)-organic framework with efficient catalytic activity in cycloaddition of CO2 and Knoevenagel condensation.

The efficient catalytic performance displayed by MOFs is decided by an appropriate charge/radius ratio of defect metal sites, large enough solvent-accessible channels and Lewis base sites capable of polarizing substrate molecules. Herein, the solvothermal self-assembly led to a highly robust nanochannel-based framework of {[In4(CPDD)2(µ3-OH)2(DMF)(H2O)2]·2DMF·5H2O}n (NUC-66) with a 56.8% void volume, which is a combination of a tetranuclear cluster [In4(µ3-OH)2(COO)10(DMF)(H2O)2] (abbreviated as {In4}) and a conjugated tetracyclic pentacarboxylic acid ligand of 4,4'-(4-(4-carboxyphenyl)pyridine-2,6-diyl)diisophthalic acid (H5CPDD). To the best of our knowledge, NUC-66 is a rarely reported {In4}-based 3D framework with embedded hierarchical triangular-microporous (2.9 Å) and hexagonal-nanoporous (12.0 Å) channels, which are shaped by six rows of {In4} clusters. After solvent exchange and vacuum drying, the surface of nanochannels in desolvated NUC-66a is modified by unsaturated In3+ ions, Npyridine atoms and µ3-OH groups, all of which display polarization ability towards polar molecules due to their Lewis acidity or basicity. The catalytic experiments performed showed that NUC-66a had high catalytic activity in the cycloaddition reactions of epoxides with CO2 under mild conditions, which should be ascribed to its structural advantages including nanoscale channels, rich bifunctional active sites, large surface areas and chemical stability. Moreover, NUC-66a, as a heterogeneous catalyst, could greatly accelerate the Knoevenagel condensation reactions of aldehydes and malononitrile. Hence, this work confirms that the development of rigid nanoporous cluster-based MOFs built on metal ions with a high charge and large radius ratio will be more likely to realize practical applications, such as catalysis, adsorption and separation of gas, etc.

Facile preparation of graphene by high-temperature electrolysis and its application in supercapacitor.

Graphene is well known owing to its astonishing properties: stronger than diamond, more conductive than copper and more flexible than rubber. Because of its potential uses in industry, researchers have been searching for less toxicity ways to make graphene in large amount with lower cost. We demonstrated an efficient method to prepare graphene by high temperature electrolysis technique. High resolution scanning electron microscopy and raman spectroscopy were used to characterize the microstructure of graphene. Graphene was assembled into the supercapacitor and its performance of electrochemical capacitor was investigated by constant current charge and discharge, cyclic voltammetry and AC impedance. The results showed that the micro-morphology of the prepared graphene was multilayer and it was favorable when the electrolytic voltage was 1.5 V. When the current density is 1 mA/cm(2), the specific capacitance of the graphene supercapacitor can reach 78.01 F/g in 6 mol/L KOH electrolyte, which was an increase of 114% compared with 36.43 F/g of conventional KOH electrolyte.

Anthracene derivative covalently immobilized on sensing membrane as a fluorescent carrier for water assay.

This article describes an optical chemical sensor based on a fluorescent dye 1-allyloxy-4-hydroxyanthracene-9, 10-dione (AHD) with terminal double bond, which is covalently bonded to quartz glass plate surface treated with a silanizing agent to prevent its leakage. The purpose of this work was to characterize and optimize the sensor for determining the water content in the acetone organic solvent. The sensor is resistant to swelling; the membrane possesses relatively long lifetime, short response and recovering time. The reversibility and reproducibility of the sensor are adequate for practical measurements.

Optimized partition of minimum spanning tree for piecewise modeling by particle swarm algorithm. QSAR studies of antagonism of angiotensin II antagonists.

In quantitative structure-activity relationship (QSAR) modeling, when compounds in a training set exhibit a significant structural distinction between each other, in particular when chemicals of biological interest interacting on the receptor involve a different mechanism, it might be difficult to construct a single linear model for the whole population of compounds of interest with desired residuals. Developing a piecewise linear local model can be effective to circumvent the aforementioned problem. In this paper, piecewise modeling by the particle swarm optimization (PMPSO) approach is applied to QSAR study. The minimum spanning tree is used for clustering all compounds in the training set to form a tree, and the modified discrete PSO is applied to divide the tree to find satisfactory piecewise linear models. A new objective function is formulated for searching the appropriate piecewise linear models. The proposed PMPSO algorithm was used to predict the antagonism of angiotensin II. The results demonstrated that PMPSO is useful for improvement of the performance of regression models.

Hybridized particle swarm algorithm for adaptive structure training of multilayer feed-forward neural network: QSAR studies of bioactivity of organic compounds.

The multilayer feed-forward ANN is an important modeling technique used in QSAR studying. The training of ANN is usually carried out only to optimize the weights of the neural network and without paying attention to the network topology. Some other strategies used to train ANN are, first, to discover an optimum structure of the network, and then to find weights for an already defined structure. These methods tend to converge to local optima, and may also lead to overfitting. In this article, a hybridized particle swarm optimization (PSO) approach was applied to the neural network structure training (HPSONN). The continuous version of PSO was used for the weight training of ANN, and the modified discrete PSO was applied to find appropriate the network architecture. The network structure and connectivity are trained simultaneously. The two versions of PSO can jointly search the global optimal ANN architecture and weights. A new objective function is formulated to determine the appropriate network architecture and optimum value of the weights. The proposed HPSONN algorithm was used to predict carcinogenic potency of aromatic amines and biological activity of a series of distamycin and distamycin-like derivatives. The results were compared to those obtained by PSO and GA training in which the network architecture was kept fixed. The comparison demonstrated that the HPSONN is a useful tool for training ANN, which converges quickly towards the optimal position, and can avoid overfitting in some extent.

Modified particle swarm optimization algorithm for variable selection in MLR and PLS modeling: QSAR studies of antagonism of angiotensin II antagonists.

A version of modified particle swarm optimization (PSO) algorithm has been proposed. The PSO algorithm has been modified to adopt to the discrete combinatorial optimization problem and reduce the probability of sinking into local optima. In the modified PSO algorithm, the velocity represents the probability of element in each particle taking value 1 or 0. The modified discrete PSO algorithm is proposed to select variables in MLR and PLS modeling and to predict antagonism of angiotensin II antagonists. The modified C(p) is employed as fitness function. The results were compared to those obtained by GAs. Experimental results have demonstrated that the modified PSO is a useful tool for variable selection which converges quickly towards the optimal position.

A reversible chemosensor for nitrite based on the fluorescence quenching of a carbazole derivative.

The carbazole derivative, with an amino group in 9-position (9-methylacryloylamino carbazole (MAC), has been utilized to prepare a fluorescent sensor and used for the determination of NO(2)(-) based on the reaction between nitrite (NO(2)(-)) and excess I(-) to form I(3)(-), which can quench the fluorescence of carbazole derivative. MAC, as a fluorescent carrier, has a terminal double bond and is covalently immobilized on a quartz glass plate surface by photo-polymerization to prevent the leakage of the dye. The sensor shows sufficient repeatability, selectivity, operational lifetime of 8 weeks, and a fast response of less then 30s. NO(2)(-) can be determined in the range between 1.0x10(-6) and 1.0x10(-4)moll(-1) with a detection limit of 8.0x10(-7)moll(-1) at pH of 2.0. The quenching mechanism is discussed. Most commonly coexisting ions do not interfer with the NO(2)(-) assay.

A coumarin derivative covalently immobilized on sensing membrane as a fluorescent carrier for nitrofurazone.

A coumarin derivative 4-methyl-8-methylacrylamide-2H, 5H-pyrano [3, 2-C] benzpyran 2, 5-dione (MMPBD) has been synthesized as a fluorescent carrier for preparing an optical chemical sensor. The carrier is immobilized on a quartz glass plate surface treated with a silanizing agent to prevent the leakage of the dye. This MMPBD sensor can be utilized for a nitrofurazone (NF) assay based on fluorescence quenching. The sensor shows good repeatability, a long lifetime and a fast response of less then 50 s. NF can be determined in the range between 1.0x10(-6)-1.0x10(-3 )mol L(-1) with a detection limit of 8.0x10(-7) mol L(-1 )at pH 7.0.