Electrospinning of Biomaterials for Vascular Regeneration

Cardiovascular diseases have been the leading cause of morbidity and mortality in the world recently. With the growing aging population accompanied by chronic diseases, such as uremia and diabetes, there is an increasing clinical demand for vascular grafts with proper performance. Although some achievements have been made in the development of tissue-engineered vascular grafts composed of natural and synthetic polymeric materials or decellularized vessels, clinical applications with a diameter of less than 6 mm are still principally derived from autografts, such as autologous saphenous veins. Many challenges remain in anti-thrombosis, rapid endothelialization, modulating the inflammatory response and inhibition of intimal hyperplasia and calcification. In the review, recent progress in the electrospinning of biodegradable polymers for vascular regeneration are summarized, especially from the view of biomechanical factors. Hybrid vascular grafts consisting of natural and synthetic polymers with multicomponent, di-or tri-layers are focused in order to provide novel experiences in biomaterials for applications in this field.     

A novel aptasensor based on 3D-inorganic hybrid composite as immobilized substrate for sensitive detection of platelet-derived growth factor

A novel electrochemical detection approach for platelet-derived growth factor(PDGF) via "sandwich"structure is reported in this paper. 3D-4MgCO_3 Mg(OH)_2 4H_2O-Au NPs inorganic hybrid composite was utilized as immobilized substrate for sensitive PDGF detection and Pt-Au bimetallic nanoparticles were labelled on PDGF aptamer to indirectly detect PDGF for the first time. The proposed aptasensor exhibited a high catalytic efficiency towards reduction of H_2O_2, hence the sensitive detection of PDGF was achieved.Results showed that the aptasensor exhibited excellent linear response to PDGF, in the range of 0.1 pg/m L–10 ng/m L(4 fmol/L–400 pmol/L), with detection limit of 0.03 pg/m L(1.2 fmol/L).     

Monomer Protonation‐Dependent Surface Polymerization to Achieve One‐Step Grafting Cross‐Linked Poly(4‐Vinylpyridine) Onto Core–Shell Fe3O4@SiO2 Nanoparticles

Functional polymer‐grafting silica nanoparticles hold great promise in diverse applications such as molecule recognition, drug delivery, and heterogeneous catalysis due to high density and uniform distribution of functional groups and their tunable spatial distance. However, conventional grafting methods from monomers mainly consist of one or more extra surface modification steps and a subsequent surface polymerization step. A monomer protonation‐dependent surface polymerization strategy is proposed to achieve one‐step uniform surface grafting of cross‐linked poly(4‐vinylpyridine) (P4VP) onto core–shell Fe₃O₄@SiO₂ nanostructures. At an approximate pH, partially protonated 4VP sites in aqueous solution can be strongly adsorbed onto deprotonated silanol groups ( Si O⁻) onto Fe₃O₄@SiO₂ nanospheres to ensure prior polymerization of these protonated 4VP sites exclusively onto Fe₃O₄@SiO₂ nanoparticles and subsequent polymerization of other 4VP and divinylbenzene monomers harvested by these protonated 4VP monomers onto Fe₃O₄@SiO₂ nanoparticles, thereby achieving direct grafting of cross‐linked P4VP macromolecules onto Fe₃O₄@SiO₂ nanoparticles.     

Step‐Growth Polymerizing Systems of General Type “AfiBgi”: Calculating the Radius of Gyration and the g‐Curve Using Generating Functions and Recurrences

Step‐growth polymerized systems of general type “AfiBgi” are considered. One or more of the monomer species carries at least three reactive groups and thus can act as a branching point in a polymeric molecule. An algorithmic method is presented to calculate the topology‐averaged square radius of gyration, R ²[s ], of the molecules in the class of s‐mers. The degree of polymerization, s , may run through its full range. In addition to R ²[s ], the shrinking factor, g [s ], is calculated. The method uses integer arithmetic, generating functions, and computer algebra.

     

Electro‐nano Diagnostic Platforms for Simultaneous Detection of Multiple Cancer Biomarkers

In this study, a bimetallic nanomaterial‐based electrochemical immunosensor was developed for the detection of carcinoembryonic antigen (CEA) and vascular endothelial growth factor (VEGF) cancer biomarkers at the same time. CEA and VEGF biomarkers are indicators for colon and breast cancers and stomach cancers, respectively. During the study, gold nanoparticle (AuNp), lead nanoparticle (PbNp), copper nanoparticle (CuNp) and magnetic gamma iron(III)oxide (γFe₂O₃ Np) were synthesized, characterized and used together for the first time in the structure of an electrochemical biosensor based on anti‐CEA and anti‐VEGF. For this purpose, Au SPE based sandwich immunosensor was fabricated by using labeled anti‐CEA (labeled with Pb⁺²) and labeled anti‐VEGF (labeled with Cu⁺²). As a result, CEA and VEGF biomarkers were detected following the oxidation peaks of label metals (Pb⁺² and Cu⁺²) by using differential pulse voltammetry. After the experimental parameters were optimized, the linear range was found in the concentration range between 25 ng/mL and 600 ng/mL with the relative standard deviation (RSD) value of (n=3 for 600 ng/mL) 3.33 % and limit of detection (LOD) value of 4.31 ng/mL for CEA biomarker. On the other hand, the linear range was found in the concentration range between 0.2 ng/mL and 12.5 ng/mL with the RSD value of (n=3 for 12.5 ng/mL) 5.31 % and LOD value of 0.014 ng/mL for VEGF biomarker. Lastly, sample application studies for synthetic plasma sample and interference studies with dopamine, ascorbic acid, BSA, cysteine and IgG were carried out.     

基于高通量解析算法的复杂样品重叠气相色谱-质谱信号的快速分析

化学计量学算法为重叠气相色谱-质谱(GC-MS)信号的解析提供了有效手段,但其在计算过程中一般需要将数据进行分段处理,然后只对信号的某些区间进行解析,难以实现真正意义上的高通量分析。该文结合移动窗口目标转换因子分析(MWTTFA)和非负免疫算法(NNIA),建立了一种高通量解析方法。首先,根据所有可能存在的目标组分的标准质谱信息,利用MWTTFA检验复杂信号中存在的组分,并确定目标组分的质谱信息和洗脱时间区域。以得到的质谱信息作为后续计算的输入值,利用NNIA解析得到相应的色谱信息。采用快速升温程序对17种和42种农药混合标准样品的GC-MS信号进行分析,利用所建立的方法可在10 min内得到全部组分的色谱和质谱信息。     

基于改进的PSO-SVM的音频信号特征识别和分类

针对音频信号准确性分类的问题,提出一种基于改进的的粒子群优化算法(PSO)的支持向量机(SVM)音频信号分类的方法,简称IPSO-SVM.首先用Mel倒谱系数法对4种音频信号进行特征提取.其次在PSO中引入自适应变异因子,能够成功地跳出局部极小值点;然后对PSO中的惯性权重进行了改进,将惯性权重由常数变为指数型递减函数.随着迭代的进行,使权重逐渐减小,这样做有利于粒子进行局部寻优.最后用改进的PSO不断优化SVM中的惩罚因子c和核函数参数g来提高预测精度.实验结果表明,与传统的SVM、PSO-SVM、GA-SVM相比,我们提出的IPSO-SVM算法分类结果更精确.     

一维六方准晶压电材料中幂函数型曲线裂纹的反平面问题

依据一维六方准晶压电材料反平面问题的基本方程,利用复变函数方法,通过引入适当的保角映射,研究了一维六方准晶压电材料中幂函数型曲线裂纹的反平面问题,并利用Cauchy积分理论,得到电不可通和电可通边界条件下的应力场和位移场的复表示以及裂纹尖端场强度因子的解析表达式.     

湖南大湘西地区城市经济竞争力比较研究

在现有城市经济竞争力分析的国内外研究成果的基础上,依据城市竞争力相关理论,借鉴国内外评价机构的评价模型和分析体系,构建出湖南省大湘西地区城市经济竞争力的评价指标体系,并利用因子分析法对大湘西地区城市经济竞争力进行综合评价,并对各个城市的经济竞争力进行比较研究.在此基础上,有针对性地提出了促进大湘西地区城市经济竞争力提升的对策建议.