Reverse genetic platform for inactivated and live-attenuated influenza vaccine

Influenza vaccine strains have been traditionally developed by annual reassortment between vaccine donor strain and the epidemic virulent strains. The classical method requires screening and genotyping of the vaccine strain among various reassortant viruses, which are usually laborious and time-consuming. Here we developed an efficient reverse genetic system to generate the 6:2 reassortant vaccine virus from cDNAs derived from the influenza RNAs. Thus, cDNAs of the two RNAs coding for surface antigens, haemagglutinin and neuraminidase from the epidemic virus and the 6 internal genes from the donor strain were transfected into cells and the infectious viruses of 6:2 defined RNA ratio were rescued. X-31 virus (a high-growth virus in embryonated eggs) and its cold-adapted strain X-31 ca were judiciously chosen as donor strains for the generation of inactivated vaccine and live-attenuated vaccine, respectively. The growth properties of these recombinant viruses in embryonated chicken eggs and MDCK cell were indistinguishable as compared to those generated by classical reassortment process. Based on the reverse genetic system, we generated 6 + 2 reassortant avian influenza vaccine strains corresponding to the A/Chicken/Korea/MS96 (H9N2) and A/Indonesia/5/2005 (H5N1). The results would serve as technical platform for the generation of both injectable inactivated vaccine and the nasal spray live attenuated vaccine for the prevention of influenza epidemics and pandemics.     

A fractional order epidemic model for the simulation of outbreaks of influenza A(H1N1)

In this paper, we propose a nonlinear fractional order model in order to explain and understand the outbreaks of influenza A(H1N1). In the fractional model, the next state depends not only upon its current state but also upon all of its historical states. Thus, the fractional model is more general than the classical epidemic models. In order to deal with the fractional derivatives of the model, we rely on the Caputo operator and on the Grünwald–Letnikov method to numerically approximate the fractional derivatives. We conclude that the nonlinear fractional order epidemic model is well suited to provide numerical results that agree very well with real data of influenza A(H1N1) at the level population. In addition, the proposed model can provide useful information for the understanding, prediction, and control of the transmission of different epidemics worldwide. Copyright © 2013 John Wiley & Sons, Ltd.     

H9N2亚型禽流感病毒细胞适应株细胞致病性和HA、NA基因序列分析

对分离自中国南方的H9N2亚型禽流感病毒A/Chicken/Guangxi/KMⅢ/99(H9N2)进行了MDCK细胞的连续传代和NA基因序列的初步分析.研究发现,病毒接种细胞36 h左右出现细胞病变(CPE),细胞肿胀变圆,聚集,脱落.流感病毒经MDCK细胞连续传代19代后,HA效价与亲代病毒相当.将传代获得的第19代病毒进行基因克隆,与亲代病毒进行序列比较,发现经传代后其HA1羧基端的分子特征是:R-S-S-R,仍属于非低致病力毒株.     

Three‐dimensional printed magnetophoretic system for the continuous flow separation of avian influenza H5N1 viruses

As a result of the low concentration of avian influenza viruses in samples for routine screening, the separation and concentration of these viruses are vital for their sensitive detection. We present a novel three‐dimensional printed magnetophoretic system for the continuous flow separation of the viruses using aptamer‐modified magnetic nanoparticles, a magnetophoretic chip, a magnetic field, and a fluidic controller. The magnetic field was designed based on finite element magnetic simulation and developed using neodymium magnets with a maximum intensity of 0.65 T and a gradient of 32 T/m for dragging the nanoparticle–virus complexes. The magnetophoretic chip was designed by SOLIDWORKS and fabricated by a three‐dimensional printer with a magnetophoretic channel for the continuous flow separation of the viruses using phosphate‐buffered saline as carrier flow. The fluidic controller was developed using a microcontroller and peristaltic pumps to inject the carrier flow and the viruses. The trajectory of the virus–nanoparticle complexes was simulated using COMSOL for optimization of the carrier flow and the magnetic field, respectively. The results showed that the H5N1 viruses could be captured, separated, and concentrated using the proposed magnetophoretic system with the separation efficiency up to 88% in a continuous flow separation time of 2 min for a sample volume of 200 μL.     

甲流病毒传播的年龄结构模型的稳定性

研究甲型H1N1流感病毒的传播规律,建立年龄结构具有接种措施的SEIR流行病模型,给出了疾病流行的阈值并证明了地方病平衡点的稳定性问题.最后根据一些实际数据,进行数值模拟进而对模型的合理性加以完善,借助模型预测下一阶段甲流爆发的可能性并提出相关应对措施.     

On a Comparative Study on Some Trigonometric Classes of Distributions by the Analysis of Practical Data Sets

The aim of this paper is twofold. Firstly, we elaborate and investigate a new trigonometric class of distribution, called the type II Tan-G class. Secondly, we perform a practical comparative evaluation of certain trigonometric classes; the Sin-G, Cos-G, Tan-G classes and the new one, with each other and with their common baseline distribution. More specifically, the usefulness and flexibility of these trigonometric classes are demonstrated through twelve practical data sets, by using the Weibull distribution as baseline. Among the data sets, two of them concern the Covid-19 pandemic in France from March to June 2020. As main results, it is shown that the related trigonometric models can outperform the former Weibull model in various cases and that the proposed type II Tan Weibull model can be, in certain situations, the best of them. The main lines of the code written in the \textsf{R} software language are provided.     

Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza

Public debates driven by incomplete scientific data where nobody can claim absolute certainty, due to the current state of scientific knowledge, are studied. The cases of evolution theory, global warming and H1N1 pandemic influenza are investigated. The first two are of controversial impact while the third is more neutral and resolved. To adopt a cautious balanced attitude based on clear but inconclusive data appears to be a lose-out strategy. In contrast overstating arguments with incorrect claims which cannot be scientifically refuted appears to be necessary but not sufficient to eventually win a public debate. The underlying key mechanisms of these puzzling and unfortunate conclusions are identified using the Galam sequential probabilistic model of opinion dynamics (Galam, 2002 [4], Galam, 2005 [18], Galam and Jacobs, 2007 [19]). It reveals that the existence of inflexible agents and their respective proportions are the instrumental parameters to determine the faith of incomplete scientific data in public debates. Acting on one’s own inflexible proportion modifies the topology of the flow diagram, which in turn can make irrelevant initial supports. On the contrary focusing on open-minded agents may be useless given some topologies. When the evidence is not as strong as claimed, the inflexibles rather than the data are found to drive the opinion of the population. The results shed a new but disturbing light on designing adequate strategies to win a public debate.     

Mathematical analysis of an influenza epidemic model,formulation of different controlling strategies using optimal control and estimation of basic reproduction number

In this article, a deterministic model is formulated to perform a thorough investigation of the transmission dynamics of influenza. In particular, our model takes into account the effects of medication as well as hospitalization. An in-depth stability analysis of the model is performed, and it is subsequently shown that the model is locally, as well as globally asymptotically stable, when R₀ > 1. It is also shown that there exists a unique endemic equilibrium whenever R₀ > 1. After estimating the effective contact rate, we estimate the basic reproduction number, using both an ordinary least squares and generalized least squares methodology. We also estimated confidence intervals for the effective contact rate using parametric bootstrapping. Furthermore, we perform uncertainty and sensitivity analysis to recognize the impact of crucial model parameters on R₀. In addition, using ideas from the optimal control theory, optimal medication and hospitalization strategies are proposed to eliminate the disease.