Catalyst-and additive-free selective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones leading to sulfonylated γ-butyrolactams

A convenient and regioselective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones has been developed to access a series of sulfonylated γ-butyrolactams.The present reaction could be efficiently conducted under catalyst-and additive-free conditions,in which C-S and C-C bonds were selectively constructed in one-pot procedure.     

Theragnostic Applications of Mammal and Plant-Derived Extracellular Vesicles: Latest Findings,Current Technologies,and Prospects

The way cells communicate is not fully understood. However, it is well-known that extracellular vesicles (EVs) are involved. Researchers initially thought that EVs were used by cells to remove cellular waste. It is now clear that EVs function as signaling molecules released by cells to communicate with one another, carrying a cargo representing the mother cell. Furthermore, these EVs can be found in all biological fluids, making them the perfect non-invasive diagnostic tool, as their cargo causes functional changes in the cells upon receiving, unlike synthetic drug carriers. EVs last longer in circulation and instigate minor immune responses, making them the perfect drug carrier. This review sheds light on the latest development in EVs isolation, characterization and, application as therapeutic cargo, novel drug loading techniques, and diagnostic tools. We also address the advancement in plant-derived EVs, their characteristics, and applications; since plant-derived EVs only recently gained focus, we listed the latest findings. Although there is much more to learn about, EV is a wide field of research; what scientists have discovered so far is fascinating. This paper is suitable for those new to the field seeking to understand EVs and those already familiar with it but wanting to review the latest findings.     

基于可切换频率选择表面的微波加热数值研究

为解决微波加热中普遍存在的加热不均匀问题,已提出模式搅拌器、旋转转盘等机械转动方法来改变加热物体中的电场分布,从而提高加热均匀性。 然而,机械转动的方法往往使得仿真计算困难并且会增加微波系统的复杂性。 因此,本文提出一种应用于微波加热的可切换频率选择表面,其工作频率为2. 45 GHz,通过调整PIN 二极管的开关状态来改变电场分布,将不同状态下的频率选择表面在时间上进行联合并加热,可以明显提高加热均匀性和效率。 计算结果表明,该频率选择表面在导通和关闭状态下的传输系数分别为-32. 10 dB 和-0. 16 dB,能将均匀性提高 43%,加热效率提高42%,有望广泛应用于工业领域。     

Dynamic Variation of Amino Acid Contents and Identification of Sterols in Xinyang Mao Jian Green Tea

As important biomolecules in Camellia sinensis L., amino acids (AAs) are considered to contribute to the overall green tea sensory quality and undergo dynamic changes during growth. However, limited by analytical capacity, detailed AAs composition in different growth stages remains unclear. To address this question, we analyzed the dynamic changes of 23 AAs during leaf growth in Xinyang Mao Jian (XYMJ) green tea. Using amino acid analyzer, we demonstrated that most AAs are abundant on Pure Brightness Day and Grain Rain Day. After Grain Rain, 23 AAs decreased significantly. Further analysis shows that theanine has a high level on the day before Spring Equinox and Grain Rain, accounting for 44–61% of the total free AAs content in tea leaves. Glu, Pro, and Asp are the second most abundant AAs. Additionally, spinasterol and 22,23-dihydrospinasterol are first purified and identified in ethanol extract of XYMJ by silica gel column chromatography method. This study reveals the relationship between plucking days and the dynamic changes of AAs during the growth stage and proves the rationality of the traditional plucking days of XYMJ green tea.     

基于矩阵束方法的传输线系统瞬态响应分析

带有频变负载的传输线系统的瞬态响应分析是电磁兼容领域的一个重要内容,特别是对于频变负载网络较为复杂或内部结构不清晰的情况,其瞬态响应的分析较为困难。本文首先在采样频率点处对频变负载端口导纳进行测量或计算得到相应的采样导纳,并采用有理函数逼近的方式对端口导纳进行等效;之后采用矩阵束(MPM)方法求解出有理逼近函数所需的极点和留数,并将其代入到分段线性递归卷积(PLRC)技术中,实现传输线和频变负载连接点处电压的分段线性递归卷积表达;最后,结合传输线方程实现带有频变负载的传输线系统的瞬态响应分析,并通过2个算例对所提方法的性能进行验证。结果表明,所提方法在计算精确度上具有明显的优势。     

An unexpected all-metal aromatic tetranuclear silver cluster in human copper chaperone Atox1

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s¹ electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag₄ cluster is Ag₄²⁺, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.     

High-performance potassium poly(heptazine imide) films for photoelectrochemical water splitting

Photoelectrochemical (PEC) water splitting is an appealing approach by which to convert solar energy into hydrogen fuel. Polymeric semiconductors have recently attracted intense interest of many scientists for PEC water splitting. The crystallinity of polymer films is regarded as the main factor that determines the conversion efficiency. Herein, potassium poly(heptazine) imide (K-PHI) films with improved crystallinity were in situ prepared on a conductive substrate as a photoanode for solar-driven water splitting. A remarkable photocurrent density of ca. 0.80 mA cm⁻² was achieved under air mass 1.5 global illumination without the use of any sacrificial agent, a performance that is ca. 20 times higher than that of the photoanode in an amorphous state, and higher than those of other related polymeric photoanodes. The boosted performance can be attributed to improved charge transfer, which has been investigated using steady state and operando approaches. This work elucidates the pivotal importance of the crystallinity of conjugated polymer semiconductors for PEC water splitting and other advanced photocatalytic applications.

Potassium poly(heptazine imide) photoanode is synthesized, and owing to the improved crystallinity, it has presented a remarkable performance for solar-driven water splitting.     

Activation of Stimulation of Interferon Genes (STING) Signal and Cancer Immunotherapy

Stimulator of interferon gene (STING), an intracellular receptor in the endoplasmic reticulum, could induce the production of cytokines such as type I interferon (IFN) by activating the cGAS-STING signal pathway. In recent years, activation of STING has shown great potential to enhance anti-tumor immunity and reshape the tumor microenvironment, which is expected to be used in tumor immunotherapy. A number of STING agonists have demonstrated promising biological activity and showed excellent synergistic anti-tumor effects in combination with other cancer therapies in preclinical studies and some clinical trials. The combination of STING agonists and ICI also showed a potent effect in improving anti-tumor immunity. In this review, we introduce the cGAS-STING signaling pathway and its effect in tumor immunity and discuss the recent strategies of activation of the STING signaling pathway and its research progress in tumor immunotherapy.     

Electrochemical Immunoassay for Tumor Marker CA19-9 Detection Based on Self-Assembled Monolayer

A CA19-9 electrochemical immunosensor was constructed using a hybrid self-assembled membrane modified with a gold electrode and applied to detect real samples. Hybrid self-assembled membranes were selected for electrode modification and used to detect antigens. First, the pretreated working electrodes were placed in a 3-mercaptopropionic acid (MPA)/β-mercaptoethanol (ME) mixture for 24 h for self-assembly. The electrodes were then placed in an EDC/NHS mixture for 1 h. Layer modification was performed by stepwise dropwise addition of CA19-9 antibody, BSA, and antigen. Differential pulse voltammetry was used to characterize this immunosensor preparation process. The assembled electrochemical immunosensor enables linear detection in the concentration range of 0.05–500 U/mL of CA19-9, and the detection limit was calculated as 0.01 U/mL. The results of the specificity measurement test showed that the signal change of the interfering substance was much lower than the response value of the detected antigen, indicating that the sensor has good specificity and strong anti-interference ability. The repeatability test results showed that the relative standard deviations were less than 5%, showing good accuracy and precision. The CA19-9 electrochemical immunosensor was used for the actual sample detection, and the experimental results of the standard serum addition method showed that the RSD values of the test concentrations were all less than 10%. The recoveries were 102.4–115.0%, indicating that the assay has high precision, good accuracy, and high potential application value.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.