人工神经网络在SARS疫情分析与预测中的应用

讨论人工神经网络在 SARS疫情分析与预测中的应用 .采用三层结构的反向传播网络 ( Backpropagation network,简称 BP网络 ) ,对 SARS在中国的传播与流行趋势及控制策略建立了网络模型 .并利用实际数据拟合参数 ,针对北京、山西的疫情进行了计算仿真 .结果表明 ,该网络模型算法收敛速度较快 ,预测精度很高     

SARS CoV内对照RNA病毒样颗粒的构建和表达

在SARS-CoV的核酸检测方法中,由于普遍缺乏安全、稳定、特异的内对照,而不能对样品处理、反转录、扩增以及定量检测实施全程监控。构建的病毒样核蛋白颗粒内对照,能够对SARS-CoV临床检测实施监控。本文通过克隆1.7Kb大肠杆菌噬菌体MS2的装配蛋白和壳蛋白基因以及SARS冠状病毒经过突变产生的270bp内对照片断,并将这些基因连接到载体pTrc99a上表达,进行纯化、定量分析、RT-PCR检测和稳定性试验。获得SARS内对照病毒样核蛋白颗粒,在人血清和SM缓冲液中37℃稳定性可达到30天,能抵抗核糖核酸酶降解。将内对照颗粒加入临床样本中一同检测,能够对检测的全过程(样品处理、反转录和PCR)有效进行监控,与SARS-CoV没有交叉反应。研究表明制备的该病毒样核蛋白颗粒稳定、安全、可靠,可作为SARS冠状病毒RT-PCR检测、定量分析的有效内对照参考品。     

Genomic variation and point mutations analysis of Indian COVID-19 patient samples submitted in GISAID database

Corona virus disease 2019 (COVID-19) endemic has havoc on the world; the causative virus of the pandemic is SARS CoV-2. Pharmaceutical companies and academic institutes are in continuous efforts to identify anti-viral therapy or vaccines, but the most significant challenge faced is the highly evolving genome of SARS CoV-2, which is imparting evolutionary selective benefits to the virus. To understand the viral mutations, we have retrieved nine hundred and thirty-four samples from different states of India via the GISAID database and analyzed the frequency of all types of point mutation in all structural, non-structural proteins, and accessory factors of SARS CoV-2. Spike glycol protein, nsp3, nsp6, nsp12, N and NS3 were the most evolving proteins. High frequency point mutations were Q496P (nsp2), A380V (nsp4), A994D (nsp3), L37F (nsp6), P323L & A97V (nsp12), Q57H (ns3), D614G (S), P13L (N), R203K (N), G204R (N) and S194L (N).     

SARS-CoV protease inhibitors design using virtual screening method from natural products libraries

Two natural products databases, the marine natural products database (MNPD) and the traditional Chinese medicines database (TCMD), were used to find novel structures of potent SARS-CoV protease inhibitors through virtual screening. Before the procedure, the databases were filtered by Lipinski's ROF and Xu's extension rules. The results were analyzed by statistic methods to eliminate the bias in target-based database screening toward higher molecular weight compounds for enhancing the hit rate. Eighteen lead compounds were recommended by the screening procedure. They were useful for experimental scientists in prioritizing drug candidates and studying the interaction mechanism. The binding mechanism was also analyzed between the best screening compound and the SARS protein.     

Resilient and agile engineering solutions to address societal challenges such as coronavirus pandemic

The world is witnessing tumultuous times as major economic powers including the US, UK, Russia, India, and most of Europe continue to be in a state of lockdown. The worst-hit sectors due to this lockdown are sales, production (manufacturing), transport (aerospace and automotive) and tourism. Lockdowns became necessary as a preventive measure to avoid the spread of the contagious and infectious “Coronavirus Disease 2019” (COVID-19). This newly identified disease is caused by a new strain of the virus being referred to as Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS CoV-2; formerly called 2019-nCoV). We review the current medical and manufacturing response to COVID-19, including advances in instrumentation, sensing, use of lasers, fumigation chambers and development of novel tools such as lab-on-the-chip using combinatorial additive and subtractive manufacturing techniques and use of molecular modelling and molecular docking in drug and vaccine discovery. We also offer perspectives on future considerations on climate change, outsourced versus indigenous manufacturing, automation, and antimicrobial resistance. Overall, this paper attempts to identify key areas where manufacturing can be employed to address societal challenges such as COVID-19.     

Effects of superspreaders in spread of epidemic

Within the standard SIR model with spatial structure, we propose two models for the superspreader. In one model, superspreaders have intrinsically strong infectiousness. In other model, they have many social connections. By Monte Carlo simulation, we obtain the percolation probability, the propagation speed, the epidemic curve, the distribution of secondary infected and the propagation path as functions of population and the density of superspreaders. By comparing the results with the data of SARS in Singapore 2003, we conclude that the latter model can explain the observation.     

北京市SARS疫情统计分析

本文对严重急性呼吸道综合症 SA RS疾病进行了统计分析 .文章首先以北京市海淀区 SARS确诊病例和疑似病例为研究对象 ,分别按照地区、人口进行了统计分析 ,得出海淀区不同小区疫情发展的显著程度 .然后利用正交试验设计 ,分别就年龄、性别、职业等因素对海淀区 SARS确诊病人和疑似病人影响程度进行了统计分析 ,得出 2 1岁到 50岁的学生和干部得病率最高的统计结果 ,这完全符合海淀区的疫情事实 .这个统计结果已经被海淀区政府“海淀区政府应急管理信息系统 ( H EMIS)”[6]采用 . H EMIS系统作为中国第一个政府应急系统在海淀区 SARS防治中起到了一定作用 [1 ] .文章最后研究了北京市每天新增的确诊病例和每天疑似病例转为确诊病例之间的相关系数 ,从它们的相关性分析可以反映出防治 SARS疫情措施的有效性 .     

北京非典型肺炎数学模型

探讨了北京非典型肺炎数学模型 ,利用动力学和非线性回归方法建立了北京非典型肺炎预测模型 .     

An efficient method for recovery of target ssDNA based on amino-modified silica-coated magnetic nanoparticles

In this paper, an improved recovery method for target ssDNA using amino-modified silica-coated magnetic nanoparticles (ASMNPs) is reported. This method takes advantages of the amino-modified silica-coated magnetic nanoparticles prepared using water-in-oil microemulsion technique, which employs amino-modified silica as the shell and iron oxide as the core of the magnetic nanoparticles. The nanoparticles have a silica surface with amino groups and can be conjugated with any desired bio-molecules through many existing amino group chemistry. In this research, a linear DNA probe was immobilized onto nanoparticles through streptavidin conjugation using covalent bonds. A target ssDNA(I) (5′-TMR-CGCATAGGGCCTCGTGATAC-3′) has been successfully recovered from a crude sample under a magnet field through their special recognition and hybridization. A designed ssDNA fragment of severe acute respiratory syndrome (SARS) virus at a much lower concentration than the target ssDNA(I) was also recovered with high efficiency and good selectivity.     

Olive-Derived Triterpenes Suppress SARS COV-2 Main Protease: A Promising Scaffold for Future Therapeutics

SARS CoV-2 pandemic is still considered a global health disaster, and newly emerged variants keep growing. A number of promising vaccines have been recently developed as a protective measure; however, cost-effective treatments are also of great importance to support this critical situation. Previously, betulinic acid has shown promising antiviral activity against SARS CoV via targeting its main protease. Herein, we investigated the inhibitory potential of this compound together with three other triterpene congeners (i.e., ursolic acid, maslinic acid, and betulin) derived from olive leaves against the viral main protease (M^pro) of the currently widespread SARS CoV-2. Interestingly, betulinic, ursolic, and maslinic acids showed significant inhibitory activity (IC₅₀ = 3.22–14.55 µM), while betulin was far less active (IC₅₀ = 89.67 µM). A comprehensive in-silico analysis (i.e., ensemble docking, molecular dynamic simulation, and binding-free energy calculation) was then performed to describe the binding mode of these compounds with the enzyme catalytic active site and determine the main essential structural features required for their inhibitory activity. Results presented in this communication indicated that this class of compounds could be considered as a promising lead scaffold for developing cost-effective anti-SARS CoV-2 therapeutics.