Analysis of the Composition of Deinagkistrodon acutus Snake Venom Based on Proteomics,and Its Antithrombotic Activity and Toxicity Studies

There is a strong correlation between the composition of Deinagkistrodon acutus venom proteins and their potential pharmacological effects. The proteomic analysis revealed 103 proteins identified through label-free proteomics from 30 different snake venom families. Phospholipase A2 (30.0%), snaclec (21.0%), antithrombin (17.8%), thrombin (8.1%) and metalloproteinases (4.2%) were the most abundant proteins. The main toxicity of Deinagkistrodon acutus venom is hematotoxicity and neurotoxicity, and it acts on the lung. Deinagkistrodon acutus venom may have anticoagulant and antithrombotic effects. In summary, the protein profile and related toxicity and pharmacological activity of Deinagkistrodon acutus venom from southwest China were put forward for the first time. In addition, we revealed the relationship between the main toxicity, pharmacological effects, and the protein components of snake venom.     

Health-Promoting Properties of Medicinal Mushrooms and Their Bioactive Compounds for the COVID-19 Era—An Appraisal: Do the Pro-Health Claims Measure Up?

Many mushroom species are consumed as food, while significant numbers are also utilised medicinally. Mushrooms are rich in nutrients and bioactive compounds. A growing body of in vitro, in vivo, and human research has revealed their therapeutic potentials, which include such properties as anti-pathogenic, antioxidant, anti-inflammatory, immunomodulatory, gut microbiota enhancement, and angiotensin-converting enzyme 2 specificity. The uses of medicinal mushrooms (MMs) as extracts in nutraceuticals and other functional food and health products are burgeoning. COVID-19 presents an opportunity to consider how, and if, specific MM compounds might be utilised therapeutically to mitigate associated risk factors, reduce disease severity, and support recovery. As vaccines become a mainstay, MMs may have the potential as an adjunct therapy to enhance immunity. In the context of COVID-19, this review explores current research about MMs to identify the key properties claimed to confer health benefits. Considered also are barriers or limitations that may impact general recommendations on MMs as therapy. It is contended that the extraction method used to isolate bioactive compounds must be a primary consideration for efficacious targeting of physiological endpoints. Mushrooms commonly available for culinary use and obtainable as a dietary supplement for medicinal purposes are included in this review. Specific properties related to these mushrooms have been considered due to their potential protective and mediating effects on human exposure to the SARS CoV-2 virus and the ensuing COVID-19 disease processes.     

Intelligent Reflecting Surface–Assisted Wireless Secret Key Generation against Multiple Eavesdroppers

In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user’s SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex–concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.     

气相色谱-质谱法分析木奶果挥发油的化学成分

采用水蒸汽蒸馏法从大戟科木奶果中提取挥发油,用气相色谱-质谱对挥发油的化学成分进行了分析。鉴定出19种化合物,占总油量的100%,用面积归一化法测定了各成分的相对百分含量。木奶果挥发油主要成分为正十六碳酸、丁基甲氧基苯、9,12-十八碳二烯酸,分别占挥发油总量的29.53%、17.47%和11.59%,三者占其总量的58.59%。     

聚乙二醇嵌段树枝状聚赖氨酸共聚物的合成及其基因载体研究

采用液相多肽合成法制备得到窄分子量分布、结构可控的生物相容性聚乙二醇嵌段共聚树枝状聚赖氨酸阳离子功能大分子(PEG-b-Dendritic PLL). 运用¹H NMR核磁共振、凝胶电泳以及荧光淬灭滴定手段对所得阳离子两嵌段大分子的化学结构及其与质粒DNA (pDNA)结合作用与复合行为进行了研究. 结果表明聚乙二醇嵌段树枝状聚赖氨酸与pDNA分子可以在缓冲溶液中形成稳定的胶束, pDNA与阳离子树枝赖氨酸嵌段通过静电相互作用形成胶束核, 其水溶性聚乙二醇嵌段形成水溶性胶束壳, 提高了阳离子大分子/pDNA复合胶束的稳定性. 同时发现随着阳离子嵌段树枝状赖氨酸代数的增加, 阳离子两嵌段大分子与pDNA的结合作用增强, 有利于其作为基因转染生物功能载体的应用.     

聚合物交联反应诱导相分离过程的光散射二维相关分析研究

采用二维相关分析技术对聚醚砜(PES)/环氧树脂/二(2,6-二甲基苯胺基)甲烷体系的相分离过程的光散射数据进行了分析研究. 分析结果表明二维光散射分析可以提供一维光散射较难得到的信息: 在该体系相分离的演化过程早期, 即扩散控制期内, 体系中较小尺寸相区的粗大化早于较大的相区. 在相分离的中后期, 较小尺寸的富集相因碰撞融合产生更大尺寸相区的变化优先于较大尺寸相区的粗大化过程. 其原因可能是: 一方面这种增长方式比较有利于体系的能量较快地降低, 另一方面是在相分离的中后期界面运动导致的流动作用影响不容忽视.     

AN ACCELERATION STRATEGY FOR RANDOMIZE-THEN-OPTIMIZE SAMPLING VIA DEEP NEURAL NETWORKS

Randomize-then-optimize (RTO) is widely used for sampling from posterior distribu-tions in Bayesian inverse problems.However,RTO can be computationally intensive for complexity problems due to repetitive evaluations of the expensive forward model and its gradient.In this work,we present a novel goal-oriented deep neural networks (DNN) sur-rogate approach to substantially reduce the computation burden of RTO.In particular,we propose to drawn the training points for the DNN-surrogate from a local approximated posterior distribution-yielding a flexible and efficient sampling algorithm that converges to the direct RTO approach.We present a Bayesian inverse problem governed by elliptic PDEs to demonstrate the computational accuracy and efficiency of our DNN-RTO ap-proach,which shows that DNN-RTO can significantly outperform the traditional RTO.     

Efficient conversion of fructose to 5-hydroxymethylfurfural over sulfated porous carbon catalyst

Sulfated porous carbon (PC-SO3H) catalyst was successfully synthesized from one-pot treatment of porous polydivinylbenzene in H2SO4 at 250 C, which exhibited very good catalytic performances in the production of 5-hydroxymethylfurfural from fructose.     

Self-supported metal sulphide nanocrystals-assembled nanosheets on carbon paper as efficient counter electrodes for quantum-dot-sensitized solar cells

Developing efficient counter electrodes (CEs) and quantum dots made of earth-abundant and non-toxic elements is essential but still challenging for quantum dot-sensitized solar cells (QDSSCs). Here, we report a facile strategy to prepare self-supported and robust CoS₂ and NiS nanocrystals-assembled nanosheets directly grown on carbon paper (MSx NS@CP) as efficient counter electrodes for QDSSCs. Such CEs integrate the merits of fast electron transfer from interconnected conductive scaffold, efficient mass transfer from hierarchically vertical nanosheet on 3D open substrate, as well as abundant highly active catalytic sites from metal sulphide nanocrystal units. As a result, QDDSCs based on such CoS₂ NS@CP and NiS NS@CP CEs achieve a PCE of 8.88% and 7.53%, respectively. The detailed analyses suggest that CoS₂ NS@CP has the highest catalytic activity and shows the lowest charger transfer resistance, leading to the highest PCE. These findings may inspire the design and exploration of other self-supported efficient CEs by integrating highly active catalysts onto 3D conductive networks for efficient QDSSCs.