Metal-polyphenol-network coated CaCO3 as pH-responsive nanocarriers to enable effective intratumoral penetration and reversal of multidrug resistance for augmented cancer treatments

Construction of multifunctional stimuli-responsive nanotherapeutics enabling improved intratumoral penetration of therapeutics and reversal of multiple-drug resistance (MDR) is potent to achieve effective cancer treatment. Herein, we report a general method to synthesize pH-dissociable calcium carbonate (CaCO₃) hollow nanoparticles with amorphous CaCO₃ as the template, gallic acid (GA) as the organic ligand, and ferrous ions as the metallic center via a one-pot coordination reaction. The obtained GA–Fe@CaCO₃ exhibits high loading efficiencies to both oxidized cisplatin prodrug and doxorubicin, yielding drug loaded GA–Fe@CaCO₃ nanotherapeutics featured in pH-responsive size shrinkage, drug release, and Fenton catalytic activity. Compared to nonresponsive GA–Fe@silica nanoparticles prepared with silica nanoparticles as the template, such GA–Fe@CaCO₃ confers significantly improved intratumoral penetration capacity. Moreover, both types of drug-loaded GA–Fe@CaCO₃ nanotherapeutics exhibit synergistic therapeutic efficacies to corresponding MDR cancer cells because of the GA–Fe mediated intracellular oxidative stress amplification that could reduce the efflux of engulfed drugs by impairing the mitochondrial-mediated production of adenosine triphosphate (ATP). As a result, it is found that the doxorubicin loaded GA–Fe@CaCO₃ exhibits superior therapeutic effect towards doxorubicin-resistant 4T1 breast tumors via combined chemodynamic and chemo-therapies. This work highlights the preparation of pH-dissociable CaCO₃-based nanotherapeutics to enable effective tumor penetration for enhanced treatment of drug-resistant tumors.

     

Interlayer Engineering of Molybdenum Trioxide toward High‐Capacity and Stable Sodium Ion Half/Full Batteries

Orthorhombic molybdenum trioxide (MoO₃) is one of the most promising anode materials for sodium‐ion batteries because of its rich chemistry associated with multiple valence states and intriguing layered structure. However, MoO₃ still suffers from the low rate capability and poor cycle induced by pulverization during de/sodiation. An ingenious two‐step synthesis strategy to fine tune the layer structure of MoO₃ targeting stable and fast sodium ionic diffusion channels is reported here. By integrating partially reduction and organic molecule intercalation methodologies, the interlayer spacing of MoO₃ is remarkably enlarged to 10.40 Å and the layer structural integration are reinforced by dimercapto groups of bismuththiol molecules. Comprehensive characterizations and density functional theory calculations prove that the intercalated bismuththiol (DMcT) molecules substantially enhanced electronic conductivity and effectively shield the electrostatic interaction between Na⁺ and the MoO₃ host by conjugated double bond, resulting in improved Na⁺ insertion/extraction kinetics. Benefiting from these features, the newly devised layered MoO₃ electrode achieves excellent long‐term cycling stability and outstanding rate performance. These achievements are of vital significance for the preparation of sodium‐ion battery anode materials with high‐rate capability and long cycling life using intercalation chemistry.     

嵌入式实时操作系统内核混合代码的自动化验证框架

"如何构造高可信的软件系统"已成为学术界和工业界的研究热点.操作系统内核作为软件系统的基础组件，它的安全可靠是构造高可信软件系统的重要环节.为了确保操作系统内核的安全可靠，将形式化方法引入到操作系统内核验证中，提出了一个自动化验证操作系统内核的框架.该验证框架包括：（1）分别对C语言程序和混合语言程序（C语言和汇编语言）进行验证；（2）在混合语言程序验证中，为汇编程序建立抽象模型，并将C语言程序和抽象模型粘合形成基于C语言验证工具可接收的验证模型；（3）从规范中提取性质，基于该自动验证工具，对性质完成自动验证；（4）该框架不限于特定的硬件架构.成功地运用该验证框架对两种不同硬件平台的嵌入式实时操作系统内核μC/OS-II进行了验证.结果显示：利用该框架在对两个不同的硬件平台上内核验证时，框架的可重复利用率很高，高达到88%，虽然其抽象模型需要根据不同的硬件平台进行重构.在对基于这两种平台的操作系统内核验证中，分别发现了10~12处缺陷.其中，在ARM平台上两处与硬件相关的问题被发现.实验表明，该方法对不同硬件平台的同一个操作系统分析验证具有一定的通用性.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Photopolymerization synthesis of polyacrylic acid dispersant with methoxysilicon end groups and its application in a nano‐SiO2 aqueous system

In order to improve the dispersity and stability of the nano‐SiO₂ aqueous system with high solid content, a kind of polyacrylic acid dispersant with methoxysilicon end groups (KH590‐PAA) was synthesized by photopolymerization of acrylic acid (AA) initiated with (3‐mercaptopropyl)trimethoxysilane (KH590). After adding KH590‐PAA into the nano‐SiO₂ aqueous dispersion system (20 wt% solid content), the viscosity and the curing time of the system were measured with a rotational viscometer and the inverted bottle method. Moreover, the dispersion mechanism of KH590‐PAA for the nano‐SiO₂ aqueous system was researched by measuring the adsorption capacity, the particle size and the zeta potential of the nanoparticles with a conductivity meter, dynamic light scattering, SEM and TEM, respectively. The results showed that the methoxysilicon groups in KH590‐PAA could react with hydroxyl groups on the surface of nano‐SiO₂ in the process of stirring, which enhanced the adsorption capacity of the dispersant and then increased the surface charge of the particles. Therefore, electrostatic repulsion and steric hindrance effects between the SiO₂ nanoparticles could be further enhanced by adding the KH590‐PAA dispersant, and then the nano‐SiO₂ aqueous system exhibited better dispersity and stability. Besides, the dispersion properties of SiO₂ nanoparticles in water were closely related to the addition amount and the molecular weight of the KH590‐PAA dispersant. © 2018 Society of Chemical Industry     

Characteristic of polysaccharides from Flammulina velutipes in vitro digestion under salivary,simulated gastric and small intestinal conditions and fermentation by human gut microbiota

In this study, in vitro digestion and fermentation of Flammulina velutipes -derived polysaccharides (FVP) were investigated. It was found that FVP mainly consisted of 48.45% glucose, 15.40% mannose, 14.60% xylose, 11.80% fucose and 9.90% galactose. The -human saliva, simulated gastric and small intestinal juices conditions did not break down the FVP. Based on in vitro fermentation tests, FVP modulated the composition of gut microbiota by elevating the amounts of Bifidobacteriaceae and Bacteroidaceae and reducing the numbers of genera Lachnospiraceae and Enterococcaceae. Meanwhile, FVP affected the synthesis of short-chain fatty acids derived from gut microbiota.     

改进HSR-FCN的服装图像识别分类算法研究

目前网络上的服装图像数量增长迅猛，对于大量服装图像实现智能分类的需求日益增加。将基于区域的全卷积网络（Region-Based Fully Convolutional Networks，R-FCN）引入到服装图像识别中，针对服装图像分类中网络训练时间长、形变服装图像识别率低的问题，提出一种新颖的改进框架HSR-FCN。新框架将R-FCN中的区域建议网络和HyperNet网络相融合，改变图片特征学习方式，使得HSR-FCN可以在更短的训练时间内达到更高的准确率。在模型中引入了空间转换网络，对输入服装图像和特征图进行了空间变换及对齐，加强了对多角度服装和形变服装的特征学习。实验结果表明，改进后的HSR-FCN模型有效地加强了对形变服装图像的学习，且在训练时间更短的情况下，比原来的网络模型R-FCN平均准确率提高了大约3个百分点，达到96.69%。