Ceria supported Ru~0-Ru~(δ+) clusters as efficient catalyst for arenes hydrogenation

Selective hydrogenation of aromatic amines,especially chemicals such as aniline and bis(4-aminocyclohexyl)methane for non-yellowing polyurethane,is of particular interests due to the extensive applications.To conquer the existing difficulties,in selective hydrogenation,,the Ru~0-Ru~(δ+)/CeO_2 catalyst with solid frustrated Lewis pairs was developed for aromatic amines hydrogenation with excellent activity and selectivity under relative milder conditions.The morphology,electronic and chemical properties,especially the Ru~O-Ru~(δ+) clusters and reducible ceria were characterized by X-ray diffraction(XRD),transmission electron microscopy(TEM),sca nning electronic microscopy(SEM),X-ray photoelectron sp ectroscopy(XPS),CO_2 tempe rature programmed deso rption(CO_2-TPD),H_2 tempe rature programmed reduction(H_2-TPR),H_2 diffuse reflectance Fourier transform infrared spectroscopy(H_2-DRIFT),Raman,etc.The 2% Ru/CeO_2 catalyst exhibited good conversion of 95% and selectivity greater than 99% toward cyclohexylamine.The volcano curve describing the activity and Ru state was found.Owning to the "acidic site isolation" by surrounding alkaline sites,condensation between the neighboring amine molecules could be effectively suppressed.The catalyst also showed good stability and applicability for other aromatic amines and heteroarenes containing different functional groups.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

A Novel Strategy for Regulating mRNA’s Degradation via Interfering the AUF1’s Binding to mRNA

The study on the mechanism and kinetics of mRNA degradation provides a new vision for chemical intervention on protein expression. The AU enrichment element (ARE) in mRNA 3′-UTR can be recognized and bound by the ARE binding protein (AU-rich Element factor (AUF1) to recruit RNase for degradation. In the present study, we proposed a novel strategy for expression regulation that interferes with the AUF1-RNA binding. A small-molecule compound, JNJ-7706621, was found to bind AUF1 protein and inhibit mRNA degradation by screening the commercial compound library. We discovered that JNJ-7706621 could inhibit the expression of AUF1 targeted gene IL8, an essential pro-inflammatory factor, by interfering with the mRNA homeostatic state. These studies provide innovative drug design strategies to regulate mRNA homeostasis.     

A Comprehensive Review of Rosmarinic Acid: From Phytochemistry to Pharmacology and Its New Insight

Polyphenolic acids are the widely occurring natural products in almost each herbal plant, among which rosmarinic acid (RA, C₁₈H₁₆O₈) is well-known, and is present in over 160 species belonging to many families, especially the Lamiaceae. Aside from this herbal ingredient, dozens of its natural derivatives have also been isolated and characterized from many natural plants. In recent years, with the increasing focus on the natural products as alternative treatments, a large number of pharmacological studies have been carried out to demonstrate the various biological activities of RA such as anti-inflammation, anti-oxidation, anti-diabetes, anti-virus, anti-tumor, neuroprotection, hepatoprotection, etc. In addition, investigations concerning its biosynthesis, extraction, analysis, clinical applications, and pharmacokinetics have also been performed. Although many achievements have been made in various research aspects, there still exist some problems or issues to be answered, especially its toxicity and bioavailability. Thus, we hope that in the case of natural products, the present review can not only provide a comprehensive understanding on RA covering its miscellaneous research fields, but also highlight some of the present issues and future perspectives worth investigating later, in order to help us utilize this polyphenolic acid more efficiently, widely, and safely.     

基于复合超构表面的宽带圆极化双功能器件设计

多功能器件的设计是推动新一代电磁系统发展的重要力量,而超构表面因其对电磁波的幅度、相位和极化等特性的灵活调控在多功能器件领域备受关注.传统的多功能超构表面是利用各向异性单元对相互正交的线极化波具有不同响应的特性,从而设计出适用于线极化的多功能器件.本文提出了一种缝隙加载的环I形复合超构表面单元,通过单元臂长和旋转角度的...     

Spider Silk-Improved Quartz-Enhanced Conductance Spectroscopy for Medical Mask Humidity Sensing

Spider silk is one of the hottest biomaterials researched currently, due to its excellent mechanical properties. This work reports a novel humidity sensing platform based on a spider silk-modified quartz tuning fork (SSM-QTF). Since spider silk is a kind of natural moisture-sensitive material, it does not demand additional sensitization. Quartz-enhanced conductance spectroscopy (QECS) was combined with the SSM-QTF to access humidity sensing sensitively. The results indicate that the resonance frequency of the SSM-QTF decreased monotonously with the ambient humidity. The detection sensitivity of the proposed SSM-QTF sensor was 12.7 ppm at 1 min. The SSM-QTF sensor showed good linearity of ~0.99. Using this sensor, we successfully measured the humidity of disposable medical masks for different periods of wearing time. The results showed that even a 20 min wearing time can lead to a >70% humidity in the mask enclosed space. It is suggested that a disposable medical mask should be changed <2 h.     

CeO2修饰Ni3S2纳米片用于高效电催化析氧

电化学水分解制氢作为重要的生产氢能的新能源技术,包括氢气析出反应(HER)和氧气析出反应(OER).然而,OER进行的是多步电子转移过程,动力学过程缓慢且过电位高,严重制约了电解水制氢的发展.因此开发低成本、高效稳定的非贵金属催化剂替代贵金属催化剂(RuO2,IrO2)来降低过电位,减少能源消耗十分必要.Ni3S2由于...     

Mulberry Ethanol Extract and Rutin Protect Alcohol-Damaged GES-1 Cells by Inhibiting the MAPK Pathway

Mulberry extract has been proven to have the effect of resisting alcohol damage, but its mechanism is still unclear. In this study, the composition of mulberry ethanol extract (MBE) was identified by LC-MS/MS and the main components of MBE were ascertained by measuring. Gastric mucosal epithelial (GES-1) cells were used to elucidate the mechanism of MBE and rutin (the central part of MBE) helped protect against alcohol damage. The results revealed that phenolics accounted for the majority of MBE, accounting for 308.6 mg/g gallic acid equivalents and 108 substances were identified, including 37 flavonoids and 50 non-flavonoids. The treatment of 400 μg/mL MBE and 320 μM rutin reduced early cell apoptosis and the content of intracellular reactive oxygen species, malondialdehyde and increased glutathione. The qPCR results indicated that the MBE inhibits the expression of genes in the mitogen-activated protein kinase (MAPK) pathway, including p38, JNK, ERK and caspase-3; rutin inhibits the expression of p38 and caspase-3. Overall, MBE was able to reduce the oxidative stress of GES-1 cells and regulated apoptosis-related genes of the MAPK pathway. This study provides information for developing anti-ethanol injury drugs or functional foods.     

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

This feature article overviews recent work on active spaces, matrix product reference states, treatment of quasidegeneracy, hybrid theory, density-coherence functionals, machine-learned functionals, spin–orbit coupling, gradients, and dipole moments.     

Double-slit diffraction of terahertz wave generated by tilted-pulse-front pumping

We propose a spatial diffraction diagnostic method via inserting a millimeter-gap double slit into the collimated terahertz beam to monitor the minute variation of the terahertz beam in strong-field terahertz sources, which is difficult to be resolved in conventional terahertz imaging systems. To verify the method, we intentionally fabricate tiny variations of the terahertz beam through tuning the iris for the infrared pumping beam before the tilted-pulse-front pumping setups.The phenomena can be well explained by the theory based on the tilted-pulse-front technique and terahertz diffraction.