ACE2, the Receptor that Enables Infection by SARS-CoV-2: Biochemistry,Structure, Allostery and Evaluation of the Potential Development of ACE2 Modulators

Angiotensin converting enzyme 2 (ACE2) is the human receptor that interacts with the spike protein of coronaviruses, including the one that produced the 2020 coronavirus pandemic (COVID-19). Thus, ACE2 is a potential target for drugs that disrupt the interaction of human cells with SARS-CoV-2 to abolish infection. There is also interest in drugs that inhibit or activate ACE2, that is, for cardiovascular disorders or colitis. Compounds binding at alternative sites could allosterically affect the interaction with the spike protein. Herein, we review biochemical, chemical biology, and structural information on ACE2, including the recent cryoEM structures of full-length ACE2. We conclude that ACE2 is very dynamic and that allosteric drugs could be developed to target ACE2. At the time of the 2020 pandemic, we suggest that available ACE2 inhibitors or activators in advanced development should be tested for their ability to allosterically displace the interaction between ACE2 and the spike protein.     

A Quest for (sila)0-4cyclopentasilylenes and their Arduengo Analogs by DFT

Silicon - Following our interest in exotic silylenes, here we compare and contrast 20 novel five-membered cyclic silylenes, including saturated (sila)0–4 cyclopentasilylenes (1–10) and...     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Collective reflection strategy for moderating conformity tendency and promoting reflective judgment performance

Reflective judgement is crucial for medical-related practitioners in dealing with controversial issues. However, the conformity phenomenon is likely to occur and interfere with reflective judgement learning during interactive activities. Effective strategies are required to moderate the conformity behaviour tendency (CBT) and improve reflective judgement performance (RJP). This study demonstrates two significant results: (a) Compared with the guided self-reflection learning strategy, the online collective reflection (OCR) learning strategy effectively weakened the learners' general CBT while dealing with professional controversial issues; and (b) a significantly negative correlation between the RJP achieved and the change of CBT in online environment was detected in the OCR group. The implications and potential applications in higher education were discussed. Further studies are needed to confirm the long-term effects and the extending application to other professional studies.     

Damage mechanism at different transpassive potentials of solution-annealed 316 and 316l stainless steels

Electrochemical impedance spectroscopy (EIS), anodic polarization and scanning electron microscopy techniques were used to investigate the damage mechanism in the transpassive potential region of AISI ...     

Two-step method to deposit ZrO2 coating on carbon fiber: Preparation,characterization, and performance in SiC composites

Recently, ceramic matrix composites reinforced by short carbon fibers (CFs) attracted increasing attentions. To further improve mechanical properties and oxidation resistances, CFs were subjected to oxidation and acidification followed by sol-gel dip-coating to deposit ZrO₂ on their surfaces. ZrO₂-C_f/SiC composites were fabricated by joint hot compression molding and sintering, compared to C_f/SiC and SiC prepared by the same method. Microstructural analyses indicated that ZrO₂ coatings were successfully deposited on CF surfaces, formed strong bonding and interfaces between CF and the matrix. Meanwhile, CFs were found uniformly distributed in SiC matrix with random orientations. Flexural curves of ZrO₂-C_f/SiC and C_f/SiC revealed the presence of “false plasticity” regions after sharp drops, which were quite different from brittle flexural behavior of SiC ceramic. Compression strength of the three samples showed step-up growth. ZrO₂-C_f/SiC exhibited the highest value, indicating the introduction of CFs and ZrO₂ coatings do have great influence on mechanical performances. After heat treatment, ZrO₂-C_f/SiC exhibited better oxidation resistance than C_f/SiC, with weight loss ratios estimated to ??3.76% and ??6.43%, respectively. These improved properties indicated that ZrO₂-C_f/SiC would be excellent alternatives to other existence materials under ultra-high temperature environments.     

Synergistic flame retardant effects of activated carbon and molybdenum oxide in poly(vinyl chloride)

The synergistic effects of activated carbon (AC) and molybdenum oxide (MoO₃) in improving the flame retardancy of poly(vinyl chloride) (PVC) were investigated. The effects of AC, MoO₃ and their mixture with a mass ratio of 1:1 on the flame retardancy and smoke suppression properties of PVC were studied using the limiting oxygen index and cone calorimeter tests. It was found that the flame retardancy of the relatively cheaper AC was slightly weaker than that of MoO₃. In addition, the incorporation of AC and MoO₃ greatly reduced the total heat release and improved smoke suppressant property of PVC composites. When the total content of AC and MoO₃ was 10 phr, PVC/AC/MoO₃ had the lowest peak heat release rate and peak smoke production rate values of 173.80 kW m^?2 and 0.1472 m² s^?1, which represented reductions of 47.3 and 59.9%, respectively, compared with those of PVC. Furthermore, thermogravimetric analysis and gel content tests were used to analyze the flame retardant mechanism of AC and MoO₃, with results showing that AC could promote early crosslinking in PVC. Char residue left after heating at 500 °C was analyzed using scanning electron microscopy and Raman spectroscopy, and the results showed that MoO₃ produced the most compact char, with the smallest and most organized carbonaceous microstructures. © 2017 Society of Chemical Industry