The effect of the third component on butadiene–propylene alternating copolymerization catalyzed by vanadium–aluminum system

The effects of five ethers and four AliBu₂OR's with varied R' on butadiene–propylene alternating copolymerization were investigated. It was found that by adding the proper third component, both the conversion and the catalytic efficiency could be increased. The effect of the third component on the valence state of vanadium ion was also studied. A model of the active center of the ternary-component catalyst system was proposed.     

Microfluidic three-dimensional biomimetic tumor model for studying breast cancer cell migration and invasion in the presence of interstitial flow

Cell migration and invasion are critical steps in cancer metastasis, which are the major cause of death in cancer patients. Tumor-associated macrophages(TAMs) and interstitial flow(IF) are two important biochemical and biomechanical cues in tumor microenvironment, play essential roles in tumor progression. However, their combined effects on tumor cell migration and invasion as well as molecular mechanism remains largely unknown. In this work, we developed a microfluidic-based 3 D breast cancer model by co-culturing tumor aggregates, macrophages, monocytes and endothelial cells within 3 D extracellular matrix in the presence of IF to study tumor cell migration and invasion. On the established platform, we can precisely control the parameters related to tumor microenvironment and observe cellular responses and interactions in real-time. When co-culture of U937 with human umbilical vein endothelial cells(HUVECs) or MDA-MB-231 cells and tri-culture of U937 with HUVECs and MDA-MB-231 cells, we found that mesenchymal-like MDA-MB-231 aggregates activated the monocytes to TAM-like phenotype macrophages. MDA-MB-231 cells and IF simultaneously enhanced the macrophages activation by the stimulation of colony-stimulating factor 1(CSF-1). The activated macrophages and IF further promoted vascular sprouting via vascular endothelial growth factor(VEGFα) signal and tumor cell invasion. This is the first attempt to study the interaction between macrophages and breast cancer cells under IF condition. Taken together, our results provide a new insight to reveal the important physiological and pathological processes of macrophages-tumor communication. Moreover, our established platform with a more mimetic 3 D breast cancer model has the potential for drug screening with more accurate results.     

A New Activation Method for Electroless Metal Plating：Palladium Laden via Bonding with Self—Assembly Monolayers

A new activation method has been developed for electroless copper plating on silicon wafer based on palladium chemisorption on SAMs of APTS without SnCl2 sensitization and roughening condition.A closely packed electroless copper film with strong adhesion is successfully formed by AFM observation.XPS study indicates that palladium chemisorption occurred via palladium chloride bonding to the pendant amino group of the SAMs.     

HG-ICP-AES法同时测定纺织品中痕量可萃取砷和汞

建立纺织品中痕量可萃取砷和汞的氢化物发生一电感耦合等离子体原子发射光谱检测法(HG-ICP-AES).对氢化物发生条件和ICP-AES工作参数进行了优化和选择.砷和汞的检出限分别为0.35、0.12μg/L,定量下限分别为0.023、0.008 mg/kg.对酸性汗液进行加标回收试验,砷和汞的回收率分别为91.1%～101.3%和92.9%～102.5%,测量结果的相对标准偏差分别为0.93%～1.34%和0.77%～1.57%(n=8).该方法基体干扰少,检出限低.     

[Cd(SS)(NN)]配合物掺杂CdS的光-电转换特性

本文报道了配合物[Cd(SS)(NN)](SS=mnt2-,1,2-二氰基乙烯-1,2-二硫醇离子.NN=phen-5,6-dione,1,10-菲咯啉-5,6-二酮)的合成.探讨了Cd(SS)(NN)的电子吸收光谱和发射光谱。研究了掺杂有配合物Cd(SS)(NN)的CdS复合膜的光-电转换特性。     

一些结构线性系统的SBE与P-SBE的比较

很多重要的结构矩阵都属于Rn或Cn上纯量积定义的Jordan代数J或者是Lie代数L.本文比较线性系统AX=B关于近似解的范数型结构向后误差(SBE)与偏结构向后误差(P-SBE).这里系数矩阵A∈J或A∈L.在给出若干预备性结果后,先对单右端项情形比较SBE与P-SBE,然后对多右端项情形比较.部分结果是Sun近期的一些结果的推广.     

非晶态固体的结构可以决定性能吗?

晶态固体的力学性能与塑性变形主要由结构缺陷,比如位错的运动决定.而在非晶态固体中结构如何决定性能,仍然是固体力学、材料学和凝聚态物理学共同关心但尚未解决的核心问题之一.传统材料学研究的经典范式为"结构决定性能".遵循这一信条,已经有大量的实验表征与理论、模拟研究,尝试将非晶态固体的某种结构特征与性能建立一一对应关系.但是,科学界对于非晶固体结构-性能关系成立与否,以及背后隐藏的规律知之甚少.本文针对非晶态固体的变形机制以及其微结构特征,基于分子动力学模拟,定量评估短程简单结构与中长程复杂结构在决定非晶态固体动力学性能方面的效用.通过海量抽样每种具体玻璃结构的激活能(标识激发难易程度),尝试将结构参数与激活能建立定量关系,从而揭示出非晶态固体结构-性能关系的隐藏主控因素为结构的空间关联,受限比几何结构本身更关键.只有某种结构在空间上呈现亚纳米级的空间关联长度,这种完备结构才有可能有效地决定非晶态固体的力学性能,而短程简单结构则无效.进一步,给出了评价非晶态固体结构预测性能有效性的普适定量方法,为建立广义无序物质的结构-性能关系提供了筛选准则.     

A Cyanine-based Liposomal Nanophotosensitizer for Enhanced Cancer Chemo-Photodynamic Therapy

Currently, chemotherapy is one of the most important treatment modalities for malignant tumors in the clinic, however, it exhibits some shortcomings, such as poor selectivity, limited efficacy and serious adverse effects. Therefore, synergistic therapy and accurate drug delivery at tumor sites become a promising strategy for achieving tumor eradication. Herein, a smart NIR fluorescence imaging-guided nanoliposome was fabricated by encapsulating a chemotherapeutic drug(doxorubicin, DOX), liposomes(L) and a near-infrared(NIR) photosensitizer(CY) to form L@CY@DOX, which could realize enhanced therapeutic efficacy of chemo-PDT in cancer therapy(PDT=photodynamic therapy). L@CY@DOX can induce mitochondrial apoptosis and produce severe toxicity at the cellular level, and L@CY@DOX can enrich in the tumor site, which significantly induces tumor death. In vitro and in vivo studies demonstrated that L@CY@DOX exhibited great antitumor efficacy compared with each one of these monotherapies, indicating that the combination of chemotherapy and PDT possessed potential development prospects and is anticipated in clinical application.     

A Comparative Loading and Release Study of Vancomycin from a Green Mesoporous Silica

Since its first use as a drug delivery system, mesoporous silica has proven to be a surprisingly efficient vehicle due to its porous structure. Unfortunately, most synthesis methods are based on using large amounts of surfactants, which are then removed by solvent extraction or heat treatment, leading to an undesired environmental impact because of the generated by-products. Hence, in the present study, we followed the synthesis of a silica material with a wormhole-like pore arrangement, using two FDA-approved substances as templates, namely Tween-20 and starch. As far as we know, it is the first study using the Tween-20/starch combo as a template for mesoporous silica synthesis. Furthermore, we investigated whether the obtained material using this novel synthesis had any potential in using it as a DDS. The material was further analyzed by XRD, TEM, FT-IR, N₂ adsorption/desorption, and DLS to investigate its physicochemical features. Vancomycin was selected as the active molecule based on the extensive research engaged towards improving its bioavailability for oral delivery. The drug was loaded onto the material by using three different approaches, assuming its full retention in the final system. Thermal analysis confirmed the successful loading of vancomycin by all means, and pore volume significantly decreased upon loading, especially in the case of the vacuum-assisted method. All methods showed a slower release rate compared to the same amount of the pure drug. Loadings by physical mixing and solvent evaporation released the whole amount of the drug in 140 min, and the material loaded by the vacuum-assisted method released only 68.2% over the same period of time, leading us to conclude that vancomycin was adsorbed deeper inside the pores. The kinetic release of the three systems followed the Higuchi model for the samples loaded by physical mixing and vacuum-assisted procedures, while the solvent evaporation loading method was in compliance with the first-order model.     

Machine Learning for Evaluating the Cytotoxicity of Mixtures of Nano-TiO2 and Heavy Metals: QSAR Model Apply Random Forest Algorithm after Clustering Analysis

With the development and application of nanomaterials, their impact on the environment and organisms has attracted attention. As a common nanomaterial, nano-titanium dioxide (nano-TiO₂) has adsorption properties to heavy metals in the environment. Quantitative structure-activity relationship (QSAR) is often used to predict the cytotoxicity of a single substance. However, there is little research on the toxicity of interaction between nanomaterials and other substances. In this study, we exposed human renal cortex proximal tubule epithelial (HK-2) cells to mixtures of eight heavy metals with nano-TiO₂, measured absorbance values by CCK-8, and calculated cell viability. PLS and two ensemble learning algorithms are used to build multiple QSAR models for data sets, and the test set R² is increased from 0.38 to 0.78 and 0.85, and RMSE is decreased from 0.18 to 0.12 and 0.10. After selecting the better random forest algorithm, the K-means clustering algorithm is used to continue to optimize the model, increasing the test set R² to 0.95 and decreasing the RMSE to 0.08 and 0.06. As a reliable machine algorithm, random forest can be used to predict the toxicity of the mixture of nano-metal oxides and heavy metals. The cluster analysis can effectively improve the stability and predictability of the model, and provide a new idea for the prediction of cytotoxicity model in the future.