Integrated Solid-Phase Extraction,Ultra-High-Performance Liquid Chromatography–Quadrupole-Orbitrap High-Resolution Mass Spectrometry,and Multidimensional Data-Mining Techniques to Unravel the Metabolic Network of Dehydrocostus Lactone in Rats

Dehydrocostus lactone (DL) is among the representative ingredients of traditional Chinese medicine (TCM), with excellent anticancer, antibacterial, and anti-inflammatory activities. In this study, an advanced strategy based on ultra-high-performance liquid chromatography–quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC–Q-Orbitrap HRMS) was integrated to comprehensively explore the metabolic fate of DL in rats. First, prior to data collection, all biological samples (plasma, urine, and feces) were concentrated and purified using solid-phase extraction (SPE) pre-treatment technology. Then, during data collection, in the full-scan (FS) data-dependent acquisition mode, FS-ddMS² was intelligently combined with FS-parent ion list (PIL)-dynamic exclusion (DE) means for targeted monitoring and deeper capture of more low-abundance ions of interest. After data acquisition, data-mining techniques such as high-resolution extracted ion chromatograms (HREICs), multiple mass defect filters (MMDFs), diagnostic product ions (DPIs), and neutral loss fragments (NLFs) were incorporated to extensively screen and profile all the metabolites in multiple dimensions. As a result, a total of 71 metabolites of DL (parent drug included) were positively or tentatively identified. The results suggested that DL in vivo mainly underwent hydration, hydroxylation, dihydrodiolation, sulfonation, methylation, dehydrogenation, dehydration, N-acetylcysteine conjugation, cysteine conjugation, glutathione conjugation, glycine conjugation, taurine conjugation, etc. With these inferences, we successfully mapped the “stepwise radiation” metabolic network of DL in rats, where several drug metabolism clusters (DMCs) were discovered. In conclusion, not only did we provide a refined strategy for inhibiting matrix effects and fully screening major-to-trace metabolites, but also give substantial data reference for mechanism investigation, in vivo distribution visualization, and safety evaluation of DL.     

Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space

Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.     

Palladium-catalyzed hydrosilylation of ynones to access silicon-stereogenic silylenones by stereospecific aromatic interaction-assisted Si–H activation

Hydrosilylation is one of the most important reactions in synthetic chemistry and ranks as a fundamental method to access organosilicon compounds in industrial and academic processes. However, the enantioselective construction of chiral-at-silicon compounds via catalytic asymmetric hydrosilylation remained limited and difficult. Here we report a highly enantioselective hydrosilylation of ynones, a type of carbonyl-activated alkynes, using a palladium catalyst with a chiral binaphthyl phosphoramidite ligand. The stereospecific hydrosilylation of ynones affords a series of silicon-stereogenic silylenones with up to 94% yield, 20:1 regioselectivity and 98:2 enantioselectivity. The density functional theory(DFT) calculations were conducted to elucidate the reaction mechanism and origin of high degree of stereoselectivity, in which the powerful potential of aromatic interaction in this reaction is highlighted by the multiple C–H-π interaction and aromatic cavity-oriented enantioselectivitydetermining step during desymmetric functionalization of Si–H bond.     

Dynamics of Information Flow between the Chinese A-Share Market and the U.S. Stock Market: From the 2008 Crisis to the COVID-19 Pandemic Period

The relationship between the Chinese market and the US market is widely concerned by researchers and investors. This paper uses transfer entropy and local random permutation (LRP) surrogates to detect the information flow dynamics between two markets. We provide a detailed analysis of the relationship between the two markets using long-term daily and weekly data. Calculations show that there is an asymmetric information flow between the two markets, in which the US market significantly affects the Chinese market. Dynamic analysis based on weekly data shows that the information flow evolves, and includes three significant periods between 2004 and 2021. We also used daily data to analyze the dynamics of information flow in detail over the three periods and found that changes in the intensity of information flow were accompanied by major events affecting the market, such as the 2008 financial crisis and the COVID-19 pandemic period. In particular, we analyzed the impact of the S&P500 index on different industry indices in the Chinese market and found that the dynamics of information flow exhibit multiple patterns. This study reveals the complex information flow between two markets from the perspective of nonlinear dynamics, thereby helping to analyze the impact of major events and providing quantitative analysis tools for investment practice.     

3-(噁唑-5-基)吲哚类天然产物生物活性及其衍生物的合成研究进展

3-(噁唑-5-基)吲哚类天然产物如Pimprinine,Streptochlorin等,广泛存在于海洋微生物中,因其具有多样的生物活性,在医药和农药领域中很有研究潜力.3-(噁唑-5-基)吲哚类天然产物的合成方法有很多研究报道,在吲哚结构上构建噁唑环是合成此类天然产物的关键.总结了已报道的3-(噁唑-5-基)吲哚类天然产物的生物活性,并对构建3-(噁唑-5-基)吲哚骨架的合成方法及部分主要反应机理进行了综述,探讨了3-(噁唑-5-基)吲哚类骨架作为一种优势活性结构在未来的应用前景.     

描述复合型疲劳裂纹扩展路径的等效模型

复合型裂纹的扩展路径不同于Ⅰ型裂纹,会沿着与初始裂纹面不同的方向扩展,扩展路径的准确预测对扩展速率的评估具有重要的作用.采用最大周向应力准则和最小应变能密度准则进行扩展路径的预测时,开裂角的误差会使裂纹不断偏离实际路径,造成最终结果的较大偏差.论文将复合裂纹在扩展过程中的弯折裂纹简化为直线裂纹,对简化过程中所产生的误差进行定量分析,并在此基础上提出了一种描述复合型裂纹扩展路径的等效修正模型.将此模型写入ABAQUS扩展有限元模块,实现了基于等效修正模型的疲劳裂纹扩展程序.通过对含中心斜裂纹板的疲劳裂纹扩展试验,验证了该模型的有效性,预测的开裂角与试验结果基本一致,所得到的载荷循环次数低于试验值,对含裂纹结构的寿命评估偏于保守.     

聚龙一号驱动Z箍缩负载内爆的简化电路模型

为方便描述聚龙一号装置与Z箍缩负载的电磁耦合过程,基于大量电参数实验数据和全电路模拟分析,建立了一个简化的集总电路模型,获得了等效电压波形和等效电阻、电感等集总参量。采用水介质三板输出线出口位置的开路电压作为等效电压,进一步拟合为正弦平方函数,峰值为3.3 MV（当前驱动器充压为65 kV）,零到峰值的时间长度为102.5ns。采用简化的流阻抗模型描述磁绝缘传输线内部空间电子流的电流损失效应。将电路程序与零维负载动力学程序耦合模拟,得到了与实验结果符合的负载电流波形,尤其电流波形的前沿和峰值符合较好,分析了电磁能转化为负载动能的过程。     

新型双阈值高g值MEMS惯性开关（英）

在保证引信勤务安全性和正常发射可靠性前提下,为实现引信小型化而设计了一种新型无源双阈值高g值MEMS惯性开关,其主要包括能够识别两种典型加速度环境（载荷1:15 000g-300 ms,载荷2：3000g-3 ms）的环境识别模块M1和为后续电路可靠供电的通电模块M2。环境识别模块M1主要通过控制带有Z型齿的质量块与对应L型挡块之间的碰撞来确定质量块的运动位移,进而控制通电模块M2的工作情况。基于两种典型加速度环境对MEMS惯性开关进行了动力学仿真并优化,仿真结果表明所设计的开关在载荷1环境下保持断开,而在载荷2环境下可靠闭合。     

激光冲击与渗碳复合工艺改善12CrNi3A钢磨损性能

为了提高12CrNi3A钢渗碳层质量及其抗磨损性能,提出了激光冲击与渗碳不同顺序复合的工艺方法。球磨实验结果表明,相比渗碳处理,激光冲击后渗碳试样的比磨损率降低了51%,而渗碳后激光冲击强化试样的比磨损率降低了13%,说明激光冲击后渗碳的复合工艺能更好地改善抗磨损性能。在摩擦系数差别不大的情况下,抗磨损性能的提升与显微硬度提高、微观组织变化有关,从这两方面讨论抗磨损性能提升的机理。研究表明:激光冲击强化可促进渗碳的过程,强化后渗碳形成的渗碳层结构致密,大量细小碳化物形成,固溶强化、第二相强化作用增强,显微硬度增大,从而提高抗磨损性能;而渗碳后激光冲击强化只使渗层表面发生了形变强化,与渗碳工艺相比,显微硬度略有提高,抗磨损性能提高有限。     

反应型次氯酸荧光探针

生物体内的次氯酸是氯离子和过氧化氢(H2O2)由髓过氧化物酶(MPO)催化生成的,是生物体内最重要的活性氧(ROS)之一,在生理过程中发挥了至关重要的作用.但是,过量的次氯酸会导致一系列生理疾病,因此有效的识别和检测次氯酸备受研究者们的青睐.与传统检测方法相比,荧光探针具有选择性好、灵敏度高、可实时监测等诸多优势,因此...