Screening and identification of Caulis Sinomenii bioactive ingredients with dual‐target NF‐κB inhibition and β2‐AR agonizing activities

Caulis Sinomenii (CS) is a valuable traditional medicine in China. Its extract can act as an anti‐inflammatory agent and a vascular smooth muscle relaxant. However, the underlying mechanisms remain unknown. In this study, we developed a simple dual‐target method based on ultra‐performance liquid chromatography/quadrupole time‐of‐flight mass spectrometry combined with a dual‐target bioactive screening assay for anti‐inflammatory and antispasmodic activities to characterize the chemical structure of various bioactive compounds of CS rapidly. Seven potential NF‐κB inhibitors were identified, including laudanosoline‐1‐O‐xylopyranose, 6‐O‐methyl‐laudanosoline‐1‐O‐glucopyranoside, menisperine, sinomenine, laurifoline, magnoflorine and norsinoacutin. Furthermore, IL‐6 and IL‐8 assays confirmed the anti‐inflammatory effects of these potential NF‐κB inhibitors, in which laudanosoline‐1‐O‐d ‐xylopyranose and menisperine were revealed as novel NF‐κB inhibitors. Among the seven identified alkaloids, three potential β₂‐adrenergic receptor agonists, including sinomenine, magnoflorine and laurifoline, were characterized using a luciferase reporter system to measure for the activity of β₂‐adrenergic receptor agonists. Finally, sinomenine, magnoflorine and laurifoline were identified not only as potential NF‐κB inhibitors but also as potential β₂‐adrenegic receptor agonists, which is the first time this has been reported. Molecular dynamic simulation and docking results suggest that the three dual‐bioactive constituents could not only inhibit Pseudomonas aeruginosa PAK strain‐induced inflammatory responses via a negative regulation of the Braf protein that participates in MAPK signaling pathway but also activate the β₂‐adrenegic receptor. These results suggest that CS extract has dual signaling activities with potential clinical application as a novel drug for asthma.     

Low band‐gap D–A conjugated copolymers based on anthradithiophene and diketopyrrolopyrrole for polymer solar cells and field‐effect transistors

Two conjugated copolymers PADT‐DPP and PADT‐FDPP based on anthradithiophene and diketopyrrolopyrrole, with thiophene and furan as the π‐conjugated bridge, respectively, were successfully synthesized and characterized. The number‐averaged molecular weights of the two polymers are 38.7 and 30.2 kg/mol, respectively. Polymers PADT‐DPP and PADT‐FDPP exhibit broad absorption bands and their optical band gaps are 1.44 and 1.50 eV, respectively. The highest occupied molecular orbital energy level of PADT‐DPP is located at ?5.03 eV while that of PADT‐FDPP is at ?5.16 eV. In field‐effect transistors, PADT‐DPP and PADT‐FDPP displayed hole mobilities of 4.7 × 10^?3 and 2.7 × 10^?3 cm²/(V s), respectively. In polymer solar cells, PADT‐DPP and PADT‐FDPP showed power conversion efficiency (PCE) of 3.44% and 0.29%, respectively. Atomic force microscopy revealed that the poor efficiency of PADT‐FDPP should be related to the large two‐phase separation in its active layer. If 1,8‐diiodooctane (DIO) was used as the solvent additive, the PCE of PADT‐DPP remained almost unchanged due to very limited morphology variation. However, the addition of DIO could remarkably elevate the PCE of PADT‐FDPP to 2.62% because of the greatly improved morphology. Our results suggest that the anthradithiophene as an electron‐donating polycyclic system is useful to construct new D–A alternating copolymers for efficient polymer solar cells. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2014 , 52, 1652–1661     

Interior estimates for the n-dimensional Abreuʼs equation

We study the Abreu?s equation in n-dimensional polytopes and derive interior estimates of solutions under the assumption of the uniform K-stability.     

Convergence of Stochastic Gradient Descent in Deep Neural Network

Stochastic gradient descent(SGD) is one of the most common optimization algorithms used in pattern recognition and machine learning.This algorithm and its variants are the preferred algorithm while optimizing parameters of deep neural network for their advantages of low storage space requirement and fast computation speed.Previous studies on convergence of these algorithms were based on some traditional assumptions in optimization problems.However,the deep neural network has its unique properties.Some assumptions are inappropriate in the actual optimization process of this kind of model.In this paper,we modify the assumptions to make them more consistent with the actual optimization process of deep neural network.Based on new assumptions,we studied the convergence and convergence rate of SGD and its two common variant algorithms.In addition,we carried out numerical experiments with LeNet-5,a common network framework,on the data set MNIST to verify the rationality of our assumptions.     

Mechanically strong and stiff supramolecular polymers enabled by fiber reinforced long-chain alkane matrix

Fiber-reinforced-concrete (FRC) mechanism refers short discrete fibers that are uniformly distributed and randomly oriented, which offers an effective way to improve the mechanical performance of concrete. In the design of supramolecular polymers, an analogous concept of FRC appears to have been considered very rarely-although fibrous structure has been frequently observed/generated during the supramolecular polymerization. In this work, we apply the alkane thermosets, octadecane (C₁₈H₃₈) and tetracosane (C₂₄H₅₀), taking the role of “concrete”, and the low-molecular-weight monomer with long alkyl chains as the essential “fiber” component, to fabricate the “fiber reinforced supramolecular polymer”. Very much like FRC mechanism in material science, the resulting fiber reinforced supramolecular polymer thus exhibit unusually high mechanical strength and stiffness, which is unprecedented in the conventional supramolecular strategy.     

Peroxidase-Like Platinum Clusters Synthesized by Ganoderma lucidum Polysaccharide for Sensitively Colorimetric Detection of Dopamine

The sensitive and selective detection of dopamine (DA) is very important for the early diagnosis of DA-related diseases. In this study, we reported the colorimetric detection of DA using Ganoderma lucidum polysaccharide (GLP) stabilized platinum nanoclusters (Pt_n-GLP NCs). When Pt₆₀₀-GLP NCs was added, 3,3’,5,5’-tetramethylbenzidine (TMB) was rapidly catalyzed and oxidized to blue oxTMB, indicating the peroxidase-like activity of Pt₆₀₀-GLP NCs. The catalytic reaction on the substrate TMB followed the Michaelis-Menton kinetics with the ping-pong mechanism. The mechanism of the colorimetric reaction was mainly due to the formation of hydroxyl radical (•OH). Furthermore, the catalytic reaction of Pt₆₀₀-GLP NCs was used in the colorimetric detection of DA. The linear range for DA was 1–100 μM and the detection limit was 0.66 μM. The sensitive detection of DA using Pt-GLP NCs with peroxidase-like activity offers a simple and practical method that may have great potential applications in the biotechnology field.     

An efficient label-free immunosensor based on ce-MoS2/AgNR composites and screen-printed electrodes for PSA detection

Journal of Solid State Electrochemistry - Label-free electrochemical immunosensors (EIs) are simple and sensitive in cancer diagnosis. Electrode materials which can offer a large specific area and...     

Sustainable and green decomposition of cyanotoxins and cyanobacteria through the development of new photocatalytic materials

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