A novel coronavirus severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) outbreak has caused a global coronavirus disease 2019 (COVID-19) pandemic, resulting in tens of thousands of ...infections and thousands of deaths worldwide. The RNA-dependent RNA polymerase (RdRp), also named nsp12 is the central component of coronaviral replication and transcription machinery, and it appears to be a primary target for the antiviral drug remdesivir. We report the cryo-electron microscopy structure of COVID-19 virus full-length nsp12 in complex with cofactors nsp7 and nsp8 at 2.9-angstrom resolution. In addition to the conserved architecture of the polymerase core of the viral polymerase family, nsp12 possesses a newly identified β-hairpin domain at its N terminus. A comparative analysis model shows how remdesivir binds to this polymerase. The structure provides a basis for the design of new antiviral therapeutics that target viral RdRp.
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is the etiological agent responsible for the global COVID-19 (coronavirus disease 2019) outbreak. The main protease of SARS-CoV-2, M
, is ...a key enzyme that plays a pivotal role in mediating viral replication and transcription. We designed and synthesized two lead compounds (
and
) targeting M
Both exhibited excellent inhibitory activity and potent anti-SARS-CoV-2 infection activity. The x-ray crystal structures of SARS-CoV-2 M
in complex with
or
, both determined at a resolution of 1.5 angstroms, showed that the aldehyde groups of
and
are covalently bound to cysteine 145 of M
Both compounds showed good pharmacokinetic properties in vivo, and
also exhibited low toxicity, which suggests that these compounds are promising drug candidates.
Non-structural proteins (nsp) constitute the SARS-CoV-2 replication and transcription complex (RTC) to play a pivotal role in the virus life cycle. Here we determine the atomic structure of a ...SARS-CoV-2 mini RTC, assembled by viral RNA-dependent RNA polymerase (RdRp, nsp12) with a template-primer RNA, nsp7 and nsp8, and two helicase molecules (nsp13-1 and nsp13-2), by cryo-electron microscopy. Two groups of mini RTCs with different conformations of nsp13-1 are identified. In both of them, nsp13-1 stabilizes overall architecture of the mini RTC by contacting with nsp13-2, which anchors the 5'-extension of RNA template, as well as interacting with nsp7-nsp8-nsp12-RNA. Orientation shifts of nsp13-1 results in its variable interactions with other components in two forms of mini RTC. The mutations on nsp13-1:nsp12 and nsp13-1:nsp13-2 interfaces prohibit the enhancement of helicase activity achieved by mini RTCs. These results provide an insight into how helicase couples with polymerase to facilitate its function in virus replication and transcription.
Nucleotide analog inhibitors, including broad-spectrum remdesivir and favipiravir, have shown promise in in vitro assays and some clinical studies for COVID-19 treatment, this despite an incomplete ...mechanistic understanding of the viral RNA-dependent RNA polymerase nsp12 drug interactions. Here, we examine the molecular basis of SARS-CoV-2 RNA replication by determining the cryo-EM structures of the stalled pre- and post- translocated polymerase complexes. Compared with the apo complex, the structures show notable structural rearrangements happening to nsp12 and its co-factors nsp7 and nsp8 to accommodate the nucleic acid, whereas there are highly conserved residues in nsp12, positioning the template and primer for an in-line attack on the incoming nucleotide. Furthermore, we investigate the inhibition mechanism of the triphosphate metabolite of remdesivir through structural and kinetic analyses. A transition model from the nsp7-nsp8 hexadecameric primase complex to the nsp12-nsp7-nsp8 polymerase complex is also proposed to provide clues for the understanding of the coronavirus transcription and replication machinery.
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•Structures of SARS-CoV-2 RNA polymerase in complexes with RNA revealed•Conformational changes in nsp8 and its interaction with the exiting RNA are observed•Incorporation and delayed-chain-termination mechanism of remdesivir is elucidated•Transition model from primase complex to polymerase complex is proposed
Cryo-EM structures of the SARS-CoV-2 RNA polymerase in complexes with RNA, before and after RNA translocation, reveals structural rearrangements that the RNA-dependent RNA polymerase (RdRp) nsp12 and its co-factors (nsp7 and nsp8) undergo to accommodate nucleic acid binding. Further insights into how the complex is inhibited by remdesivir, and into the primase to polymerase transition, are also presented.
•The membrane electrode was used as the catalytic electrode.•The static state and flow dynamics of electrolyte solution were compared and analyzed.•The image characterization of hydrogen bubble ...evolution in PEM membrane electrode during actual operation was studied.
Ultrasonic technology has a significant degassing effect and can increase the efficiency of hydrogen production in the proton exchange membrane electrolysis of water. However, further research is needed to understand its influence mechanism on hydrogen bubbles. In this work, a kinetic analysis is performed to investigate the principle of hydrogen production and the kinetic behaviour of hydrogen bubble evolution by applying the ultrasonic amplification technique under static and flow dynamics in the proton exchange membrane electrolysis cell. The evolution of hydrogen bubbles in the static and in the flow dynamic of the aqueous electrolyte solution under ultrasound was characterised by imaging. The results show that the aqueous electrolyte solution in the flow state reduces the size of hydrogen bubbles and increases the detachment speed compared to the static state, which promotes the process of hydrogen bubble evolution, and that the thermal effect of ultrasound on the temperature of the aqueous electrolyte solution in the flow state is very small compared to the static state and can be ignored. Ultrasound has different effects on the different stages of hydrogen bubble evolution. In the nucleation stage, the ultrasonic cavitation effect increases the highly reactive radicals such as •OH, H•, etc., and the mechanical vibration effect of ultrasound increases the nucleation sites, which are denser and more evenly distributed. In the growth phase, the ultrasonic cavitation effect and the mechanical vibration effect promote the breaking of hydrogen bonds of water molecules and improve mass transport, which promotes the growth of hydrogen bubbles, and the fluctuating energy of positive and negative ultrasound promotes the growth of hydrogen bubbles with the vibration speed. In the detachment phase, the radius of the hydrogen bubbles is influenced by the ultrasound. The radius of the hydrogen bubbles changes with the positive and negative ultrasonic pressure, the radius of the hydrogen bubbles at negative ultrasonic pressure increases, the positive ultrasonic pressure decreases, the changing effect of the radius of the hydrogen bubbles favours the detachment of the hydrogen bubbles. In the polymerisation phase, the ultrasound leads to increased polymerisation of the fine bubble streams. Ultrasound contributes to the hydrogen production effect of proton exchange membrane water electrolysis in actual operation.
The antineoplastic drug carmofur is shown to inhibit the SARS-CoV-2 main protease (M
). Here, the X-ray crystal structure of M
in complex with carmofur reveals that the carbonyl reactive group of ...carmofur is covalently bound to catalytic Cys145, whereas its fatty acid tail occupies the hydrophobic S2 subsite. Carmofur inhibits viral replication in cells (EC
= 24.30 μM) and is a promising lead compound to develop new antiviral treatment for COVID-19.
•Acoustic cavitation and impact effects generated by the ultrasonic field promote the detachment of hydrogen bubbles from the surface of the catalytic layer.•The evolutionary stages of hydrogen ...bubbles include nucleation, adherent growth, detachment and even polymerization.•Energy and mechanical analyses were used to reveal the mechanism and evolution of hydrogen bubbles.•The influence of working temperature on hydrogen bubble parameters (nucleation frequency, bubble radius, growth rate, etc) was studied.
To improve the hydrogen precipitation performance on the surface of the catalytic layer of the proton exchange membrane (PEM) hydrogen cathode, ultrasonic vibration was employed to accelerate the detachment of hydrogen bubbles on the surface of the catalytic layer. Based on the energy and mechanical analyses of nano and microbubbles, the hydrogen bubble generation mechanism and the effect of temperature on bubble parameters during the evolution process when the ultrasonic field is coupled with the electric field are investigated. The nucleation frequency of the hydrogen bubbles, the relationship between the pressure and temperature and the operating temperature during the generation and detachment of bubbles as well as the detachment radius of bubbles under the action of the ultrasonic field are obtained. The effects of ultrasound and temperature on hydrogen production were verified by visual experiments. The results show that the operating temperature affects the nucleation, growth, and detachment processes of hydrogen bubbles. The effect of temperature on the nucleation frequency of bubbles mainly comes from the Gibbs free energy required for the electrolysis reaction. The bubble radius and growth rate are both related to the temperature to the power of one-third. Ultrasonic waves enhance the separation of hydrogen bubbles from the catalyst surface by acoustic cavitation and impact effects. An increase in the working temperature reduces the activation energy barriers to be overcome for the electrolysis reaction of water, which together with a decrease in the Gibbs free energy and the surface tension coefficient, leads to an increase in the nucleation frequency of the catalytic layer and a decrease in the radius of bubble detachment, and thus improves the hydrogen precipitation performance. Visualization experiments show that in actual PEM hydrogen production, ultrasonic intensification can promote the formation of nucleation sites. The ultrasonic induced fine bubble flow not only has a drag effect on the bubble, but also intensifies the polymerization growth of the bubble due to the impact of the fine bubble flow, thus speeding up the detachment of the bubble, shortening the covering time of the hydrogen bubble on the surface of the catalytic electrode, reducing the activation voltage loss and improve the hydrogen production efficiency of PEM. The experimental results show that when the electrolyte is 60°C, the maximum hydrogen production efficiency of ultrasound is increased by 7.34%, and the average hydrogen production efficiency is increased by 5.83%.
•A radiomics approach is applied for pediatric posterior fossa tumor differentiation.•300 multimodal features are extracted to describe the statistics of the MRIs.•Machine learning methods are ...combined for effective assisted clinical diagnosis.
Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With the development of high-performance computing and machine learning technologies, radiomics provides increasing opportunities for clinical decision-making. Several studies have applied radiomics as a decision support tool in intracranial tumors differentiation. Here we seek to achieve preoperative differentiation between ependymoma (EP) and pilocytic astrocytoma (PA) using radiomics analysis method based on machine learning. A total of 135 Magnetic Resonance Imaging (MRI) slices are divided into training sets and validation sets. Three kinds of radiomics features, including Gabor transform, texture and wavelet transform based ones are used to obtain 300 multimodal features. Kruskal–Wallis test score (KWT) and support vector machines (SVM) are applied for feature selection and tumor differentiation. The performance is investigated via accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) analysis. Results show that the accuracy, sensitivity, specificity, and AUC of the selected feature set are 0.8775, 0.9292, 0.8000, and 0.8646 respectively, having no significantdifferencescomparedwiththe overall feature set. For different types of features, texture features yield the best differentiation performance and the significance analysis results are consistent with this. Our study demonstrates texture features perform better than the other features. The radiomics approach based on machine learning is efficient for pediatric posterior fossa tumors differentiation and could enhance the application of radiomics methods for assisted clinical diagnosis.
Abstract
The rigid-flexible coupling cable system under large deformation is studied, and the beam element from absolute node coordinate formulation is used to establish flexible cable body of the ...system. Different numerical integral algorithms are discussed for solving the rigid-flexible cable system and an integration strategy which combines Implicit Euler with Minimum Residual Method (MINRES) is proposed. The influence of the position and number of rigid components and different the lengths of the flexible elements on the system dynamics are analyzed. With constant total mass of the system, higher number of rigid components and their uniform distribution contribute to stabilization of the swing of the flexible cable body. When the total length of the cable is constant, increasing the number of beam elements enhances the nonlinear characteristics of the swing motion and damages the stability. The influence of different factors on the movement of large deformation flexible cable body is obtained through modeling and simulation of the rigid-flexible coupling cable system.
Cellular Automaton (CA) is widely used because of its ability to simulate complex spatiotemporal dynamic processes through applying simple rules. The basis of the CA model is the definition of ...transformation rules. During a simulation process, the rules determine the change of the cell state. However, existing processing methods calculate the driving factors based on single-point time (start time or end time), making it difficult to reflect the fact that numerous driving factors affecting the cell conversion dynamically change with time. Based on the time dynamics perspective and the data set of multiple time series, this paper designs a method of dynamic adjustment of driving factors of urban expansion on the local cell-scale. It uses linear, exponential, logarithmic, and polynomial fitting to develop a CA model of dynamic adjustment that conforms to the characteristics of local spatial evolution. The main conclusions of the paper are as follows: (1) The polynomial fitting has the highest average R2, indicating that the driving factors experiences large fluctuations over time; (2) Secondly, the simulation result kappa obtained by the four fitting methods is between 0.781–0.810, which is higher than the simulation accuracy obtained by using only a single time point. In other words, the factor does not dynamically fit with time and (3) The fitting accuracy of road density is a key indicator of correct and incorrect simulation parts of construction land. Our results demonstrate that the precision of the CA model may be significantly improved by capturing the time development law of environmental variables affecting urban development at the micro-scale.
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