Molecular basis of the structure and function of H1 hemagglutinin of influenza virus

Influenza virus hemagglutinin (HA) contains antigenic sites recognized by the host immune system, cleavage sites cleaved by host proteases, receptor binding sites attaching to sialyl receptors on the target cell, and fusion peptides mediating membrane fusion. Change in an amino acid(s) in these sites may affect the potential of virus infection and spread within and between hosts. Influenza viruses with H1 HA infect birds, pigs and humans and have caused two of the four pandemics in the past 100 years: 1918 pandemic that killed 21-50 million people and 2009 pandemic that caused more than 18,000 deaths. Understanding the relationship between antigenic structure and immune specificity, the receptor binding specificity in virus transmission, how the cleavage site controls pathogenicity, and how the fusion peptide causes membrane fusion for the entry of influenza virus into the host cell should provide information to find more effective ways to prevent and control influenza.     

A mathematical framework for critical transitions: Bifurcations, fast-slow systems and stochastic dynamics

Bifurcations can cause dynamical systems with slowly varying parameters to transition to far-away attractors. The terms “critical transition” or “tipping point” have been used to describe this situation. Critical transitions have been observed in an astonishingly diverse set of applications from ecosystems and climate change to medicine and finance. The main goal of this paper is to give an overview which standard mathematical theories can be applied to critical transitions. We shall focus on early-warning signs that have been suggested to predict critical transitions and point out what mathematical theory can provide in this context. Starting from classical bifurcation theory and incorporating multiple time scale dynamics one can give a detailed analysis of local bifurcations that induce critical transitions. We suggest that the mathematical theory of fast-slow systems provides a natural definition of critical transitions. Since noise often plays a crucial role near critical transitions the next step is to consider stochastic fast-slow systems. The interplay between sample path techniques, partial differential equations and random dynamical systems is highlighted. Each viewpoint provides potential early-warning signs for critical transitions. Since increasing variance has been suggested as an early-warning sign we examine it in the context of normal forms analytically, numerically and geometrically; we also consider autocorrelation numerically. Hence we demonstrate the applicability of early-warning signs for generic models. We end with suggestions for future directions of the theory.     

Bounds on the fine structure constantvariability from Fe ii absorption lines in QSO spectra

The dispersal of individuals of a species is the key driving force of various spatiotemporal phenomena which occur on geographical scales. It can synchronise populations of interacting species, stabilise them, and diversify gene pools [1-3]. The geographic spread of human infectious diseases such as influenza, measles and the recent severe acute respiratory syndrome (SARS) is essentially promoted by human travel which occurs on many length scales and is sustained by a variety of means of transportation [4-8]. In the light of increasing international trade, intensified human traffic, and an imminent influenza A pandemic the knowledge of dynamical and statistical properties of human dispersal is of fundamental importance and acute [7,9,10]. A quantitative statistical theory for human travel and concomitant reliable forecasts would substantially improve and extend existing prevention strategies. Despite its crucial role, a quantitative assessment of human dispersal remains elusive and the opinion that humans disperse diffusively still prevails in many models [11]. In this chapter I will report on a recently developed technique which permits a solid and quantitative assessment of human dispersal on geographical scales [11]. The key idea is to infer the statistical properties of human travel by analysing the geographic circulation of individual bank notes for which comprehensive datasets are collected at the online bill-tracking website www.wheresgeorge.com. The analysis shows that the distribution of travelling distances decays as a power law, indicating that the movement of bank notes is reminiscent of superdiffusive, scale free random walks known as Lèvy flights [13]. Secondly, the probability of remaining in a small, spatially confined region for a time T is dominated by heavy tails which attenuate superdiffusive dispersal. I will show that the dispersal of bank notes can be described on many spatiotemporal scales by a two parameter continuous time random walk (CTRW) model to a surprising accuracy. To this end, I will provide a brief introduction to continuous time random walk theory [14] and will show that human dispersal is an ambivalent, effectively superdiffusive process.     

Quantifying the transmission potential of pandemic influenza

This article reviews quantitative methods to estimate the basic reproduction number of pandemic influenza, a key threshold quantity to help determine the intensity of interventions required to control the disease. Although it is difficult to assess the transmission potential of a probable future pandemic, historical epidemiologic data is readily available from previous pandemics, and as a reference quantity for future pandemic planning, mathematical and statistical analyses of historical data are crucial. In particular, because many historical records tend to document only the temporal distribution of cases or deaths (i.e. epidemic curve), our review focuses on methods to maximize the utility of time-evolution data and to clarify the detailed mechanisms of the spread of influenza.

First, we highlight structured epidemic models and their parameter estimation method which can quantify the detailed disease dynamics including those we cannot observe directly. Duration-structured epidemic systems are subsequently presented, offering firm understanding of the definition of the basic and effective reproduction numbers. When the initial growth phase of an epidemic is investigated, the distribution of the generation time is key statistical information to appropriately estimate the transmission potential using the intrinsic growth rate. Applications of stochastic processes are also highlighted to estimate the transmission potential using similar data. Critically important characteristics of influenza data are subsequently summarized, followed by our conclusions to suggest potential future methodological improvements.     

基于相位匹配的量子行走搜索算法及电路实现

量子行走是经典随机行走在量子力学框架下的对应, 理论上可以用来解决一类无序数据库的搜索问题. 因为携带信息的量子态的扩散速度与经典相比有二次方式的增长, 所以量子行走优于经典随机行走, 量子行走的特性值得加以利用. 量子行走作为一种新发现的物理现象的数学描述, 引发了一种新的思维方式, 孕育了一种新的理论计算模型. 最新研究表明, 量子行走本身也是一种通用计算模型, 可被视为设计量子算法的高级工具, 因此受到部分计算机理论科学领域学者的关注和研究. 对于多数问题求解方案的量子算法的设计, 理论上可以只在量子行走模型下进行考虑. 基于Grover算法的相位匹配条件, 本文提出了一个新的基于量子行走的搜索算法. 理论演算表明: 一般情况下本算法的时间复杂度与Grover算法相同, 但是当搜索的目标数目多于总数的1/3时, 本算法搜索成功的概率要大于Grover算法. 本文不但利用Grover算法中相位匹配条件构造了一个新的量子行走搜索算法, 而且在本研究室原有的量子电路设计研究成果的基础上给出了该算法的量子电路表述.     

The first influenza pandemic in the new millennium: lessons learned hitherto for current control efforts and overall pandemic preparedness

Influenza viruses pose a permanent threat to human populations due to their ability to constantly adapt to impact immunologically susceptible individuals in the forms of epidemic and pandemics through antigenic drifts and antigenic shifts, respectively. Pandemic influenza preparedness is a critical step in responding to future influenza outbreaks. In this regard, responding to the current pandemic and preparing for future ones requires critical planning for the early phases where there is no availability of pandemic vaccine with rapid deployment of medical supplies for personal protection, antivirals, antibiotics and social distancing measures. In addition, it has become clear that responding to the current pandemic or preparing for future ones, nation states need to develop or strengthen their laboratory capability for influenza diagnosis as well as begin preparing their vaccine/antiviral deployment plans. Vaccine deployment plans are the critical missing link in pandemic preparedness and response. Rapid containment efforts are not effective and instead mitigation efforts should lead pandemic control efforts. We suggest that development of vaccine/antiviral deployment plans is a key preparedness step that allows nations identify logistic gaps in their response capacity.     

氧化石墨烯修饰腐蚀型长周期光纤光栅的禽流感病毒免疫传感器

提出了一种使用基于氧化石墨烯修饰包层腐蚀型长周期光纤光栅应用于检测禽流感病毒的免疫传感器.氧化石墨烯通过氢键结合在包层腐蚀型长周期光纤光栅表面上,并通过共价键将禽流感病毒单克隆抗体与氧化石墨烯表面的羧基相结合.利用氧化石墨烯上吸附的禽流感病毒单克隆抗体与禽流感病毒抗原的特异性结合引起的长周期光纤光栅谐振波长变化进行检测.结果表明,该氧化石墨烯修饰包层腐蚀型长周期光纤光栅免疫传感器对禽流感病毒的检测极限为40 ng/mL,传感器的解离常数为~1.6×10^-7 mol/L,检测范围为40 ng/mL^200μg/mL.通过对禽流感病毒空白尿囊液、禽流感病毒尿囊液和新城疫病毒尿囊液进行检测,表明免疫传感器具有良好的特异性和临床性.该免疫传感器具有应用于禽流感病毒的快速和早期诊断的可能.     

Immunity in the ABM-DSGE Framework for Preventing and Controlling Epidemics—Validation of Results

The COVID-19 pandemic has raised many questions on how to manage an epidemiological and economic crisis around the world. Since the beginning of the COVID-19 pandemic, scientists and policy makers have been asking how effective lockdowns are in preventing and controlling the spread of the virus. In the absence of vaccines, the regulators lacked any plausible alternatives. Nevertheless, after the introduction of vaccinations, to what extent the conclusions of these analyses are still valid should be considered. In this paper, we present a study on the effect of vaccinations within the dynamic stochastic general equilibrium model with an agent-based epidemic component. Thus, we validated the results regarding the need to use lockdowns as an efficient tool for preventing and controlling epidemics that were obtained in November 2020.     

An effective Hamiltonian approach to quantum random walk

In this article we present an effective Hamiltonian approach for discrete time quantum random walk. A form of the Hamiltonian for one-dimensional quantum walk has been prescribed, utilizing the fact that Hamiltonians are generators of time translations. Then an attempt has been made to generalize the techniques to higher dimensions. We find that the Hamiltonian can be written as the sum of a Weyl Hamiltonian and a Dirac comb potential. The time evolution operator obtained from this prescribed Hamiltonian is in complete agreement with that of the standard approach. But in higher dimension we find that the time evolution operator is additive, instead of being multiplicative (see Chandrashekar, Sci. Rep. 3, 2829 (18)). We showed that in the case of two-step walk, the time evolution operator effectively can have multiplicative form. In the case of a square lattice, quantum walk has been studied computationally for different coins and the results for both the additive and the multiplicative approaches have been compared. Using the graphene Hamiltonian, the walk has been studied on a graphene lattice and we conclude the preference of additive approach over the multiplicative one.     

Influenza virus pathogenicity regulated by host cellular proteases,cytokines and metabolites,and its therapeutic options

Influenza A virus (IAV) causes significant morbidity and mortality. The knowledge gained within the last decade on the pandemic IAV(H1N1)2009 improved our understanding not only of the viral pathogenicity but also the host cellular factors involved in the pathogenicity of multiorgan failure (MOF), such as cellular trypsin-type hemagglutinin (HA₀) processing proteases for viral multiplication, cytokine storm, metabolic disorders and energy crisis. The HA processing proteases in the airway and organs for all IAV known to date have been identified. Recently, a new concept on the pathogenicity of MOF, the “influenza virus–cytokine–trypsin” cycle, has been proposed involving up-regulation of trypsin through pro-inflammatory cytokines, and potentiation of viral multiplication in various organs. Furthermore, the relationship between causative factors has been summarized as the “influenza virus–cytokine–trypsin” cycle interconnected with the “metabolic disorders–cytokine” cycle. These cycles provide new treatment concepts for ATP crisis and MOF. This review discusses IAV pathogenicity on cellular proteases, cytokines, metabolites and therapeutic options.     

Shape-controlled synthesis of diamond crystal by epitaxial growth under high pressure and high temperature conditions

In this paper, the diamond epitaxial growth mechanism has been studied in detail by employing several types of diamond as a seed in a catalyst-graphite system under high pressure and high temperature (HPHT) conditions. We find that the diamond nucleation, growth rate, crystal orientation, and morphology are significantly influenced by the original seeds. The smooth surfaces of seeds are beneficial for the fabrication of high-quality diamond. Our results reveal that the diamond morphology is mainly determined by the original shape of seeds in the early growth stage, but it has an adjustment process during the growth and leads to well symmetry. Additionally, we have also established the growth model for the twinned diamond grown on several seeds, and proposed the possible growth processes by tracking the particular shapes of seeds before and after treatment under HPHT conditions. These results suggest that the shape-controlled synthesis of diamond with well morphology can be realized by employing certain suitable diamond seeds. This work is expected to play an important role in the preparation of trustworthy diamond-based electronic and photonic devices.     

Rheology of interfacial protein-polysaccharide composites

The aim of this paper is to check feasibility of using the maximal-entropy random walk in algorithms finding communities in complex networks. A number of such algorithms exploit an ordinary or a biased random walk for this purpose. Their key part is a (dis)similarity matrix, according to which nodes are grouped. This study en- compasses the use of a stochastic matrix of a random walk, its mean first-passage time matrix, and a matrix of weighted paths count. We briefly indicate the connection between those quantities and propose substituting the maximal-entropy random walk for the previously chosen models. This unique random walk maximises the entropy of ensembles of paths of given length and endpoints, which results in equiprobability of those paths. We compare the performance of the selected algorithms on LFR benchmark graphs. The results show that the change in performance depends very strongly on the particular algorithm, and can lead to slight improvements as well as to significant deterioration.     

甲型流感病毒DNA序列的长记忆ARFIMA模型

流感病毒分为三类:甲型(A型),乙型(B型),丙型(C型).在这三种类型中甲型(A型)流感病毒是最致命的流感病毒,对人类引起了严重疾病.本文对甲型流感病毒DNA序列建立了一种新的时间序列模型,即CGR(Chaos Game Representation)弧度序列.利用CGR坐标将甲流病毒DNA序列转换成CGR弧度序列,且引入长记忆ARFIMA模型去拟合此类序列,发现随机找来的10条H1N1序列,10条H3N2序列都具有长相关性且拟合很好,并且还发现这两种序列可以尝试用不同的ARFIMA模型去识别,其中H1 关键词： 甲型流感 时间序列模型 CGR (p')" href="#">ARFIMA(p d 模型')" href="#">q)模型     

Enhancing the synchronizability of networks by rewiring based on tabu search and a local greedy algorithm

By considering the eigenratio of the Laplacian matrix as the synchronizability measure, this paper presents an efficient method to enhance the synchronizability of undirected and unweighted networks via rewiring. The rewiring method combines the use of tabu search and a local greedy algorithm so that an effective search of solutions can be achieved. As demonstrated in the simulation results, the performance of the proposed approach outperforms the existing methods for a large variety of initial networks, both in terms of speed and quality of solutions.     

Noise-induced stabilization of bumps in systems with long-range spatial coupling

The position of a localized region of active neurons (a “bump”) has been proposed to encode information for working memory, the head direction system, and feature selectivity in the visual system. Stationary bumps are ordinarily stable, but including spike frequency adaptation in the neural dynamics causes a stationary bump to become unstable to a moving bump through a supercritical pitchfork bifurcation in bump speed. Adding spatiotemporal noise to the network supporting the bump can cause the average speed of the bump to decrease to almost zero, reversing the effect of the adaptation and “restabilizing” the bump. This restabilizing occurs for noise levels lower than those required to break up the bump. The restabilizing can be understood by examining the effects of noise on the normal form of the pitchfork bifurcation where the variable involved in the bifurcation is bump speed. This noisy normal form can be further simplified to a persistent random walk in which the probability of changing direction is related to the noise level through an Arrhenius-type rate. The probability density function of position for the continuous-time version of this random walk satisfies the telegrapher’s equation, and the closed-form solution of this PDE allows us to find expressions for the mean and variance of the average speed of the particle (the bump) undergoing the random walk. This noise-induced stabilization is a novel example in which moderate amounts of noise have a beneficial effect on a system, specifically, stabilizing a spatiotemporal pattern.     

Simultaneous extraction of multiple orientational constraints of membrane proteins by 13C-detected N-H dipolar couplings under magic angle spinning

A 13C-detected N-H dipolar coupling technique is introduced for uniaxially mobile membrane proteins for orientation determination using unoriented samples. For proteins undergoing rigid-body uniaxial rotation in the lipid bilayer, the intrinsic equality between the dipolar coupling constants measured in unoriented samples and the anisotropic coupling measured in static oriented samples has been shown recently. Here, we demonstrate that the orientation-sensitive backbone N-H dipolar couplings can be measured with 13C detection using 2D and 3D MAS correlation experiments, so that maximal site resolution can be achieved and multiple orientational constraints can be extracted from each experiment. We demonstrate this technique on the M2 transmembrane peptide of the influenza A virus, where the N-H dipolar couplings of various residues fit to a dipolar wave for a helical tilt angle of 37 degrees , in excellent agreement with data obtained from singly 15N-labeled samples.     

血凝素蛋白及抗体相互作用的太赫兹光谱主成分分析

采用太赫兹时域光谱系统, 测量了7种不同浓度的血凝素蛋白及其与特异性抗体、无关抗体对照组反应的透射光谱, 采用光谱预处理及主成分分析法, 对多个太赫兹光谱参数进行分析. 结果显示, 主成分分析在数据降维的同时, 可以突出数据的主要变化趋势; 在原始变量相关性一致的条件下, 约化吸收截面与血凝素蛋白浓度之间表现出最强的相关性, 而介电损耗角正切值更适合于对血凝素蛋白-抗体复合物的聚类效果进行定性分析. 该研究表明主成分分析法对于太赫兹生物光谱的分析及进一步研究蛋白质的结构和功能具有重要的指导意义.     

Investigation of continuous-time quantum walk by using Krylov subspace-Lanczos algorithm

In papers [Jafarizadehn and Salimi, Ann. Phys. 322, 1005 (2007) and J. Phys. A: Math. Gen. 39, 13295 (2006)], the amplitudes of continuous-time quantum walk (CTQW) on graphs possessing quantum decomposition (QD graphs) have been calculated by a new method based on spectral distribution associated with their adjacency matrix. Here in this paper, it is shown that the CTQW on any arbitrary graph can be investigated by spectral analysis method, simply by using Krylov subspace-Lanczos algorithm to generate orthonormal bases of Hilbert space of quantum walk isomorphic to orthogonal polynomials. Also new type of graphs possessing generalized quantum decomposition (GQD) have been introduced, where this is achieved simply by relaxing some of the constrains imposed on QD graphs and it is shown that both in QD and GQD graphs, the unit vectors of strata are identical with the orthonormal basis produced by Lanczos algorithm. Moreover, it is shown that probability amplitude of observing the walk at a given vertex is proportional to its coefficient in the corresponding unit vector of its stratum, and it can be written in terms of the amplitude of its stratum. The capability of Lanczos-based algorithm for evaluation of CTQW on graphs (GQD or non-QD types), has been tested by calculating the probability amplitudes of quantum walk on some interesting finite (infinite) graph of GQD type and finite (infinite) path graph of non-GQD type, where the asymptotic behavior of the probability amplitudes at the limit of the large number of vertices, are in agreement with those of central limit theorem of [Phys. Rev. E 72, 026113 (2005)]. At the end, some applications of the method such as implementation of quantum search algorithms, calculating the resistance between two nodes in regular networks and applications in solid state and condensed matter physics, have been discussed, where in all of them, the Lanczos algorithm, reduces the Hilbert space to some smaller subspaces and the problem is investigated in the subspace with maximal dimension.     

Radiation-induced robust oscillation [2mm]and non-Gaussian fluctuation

There have been many recent studies devoted to the consequences of stochasticity in protein circuitry. Stress conditions, including DNA damage, hypoxia, heat shock, nutrient deprivation, and oncogene activation, can result in the activation and accumulation of p53. Several experimental studies show that oscillations can be induced by DNA damage following nuclear irradiation. To explore the underlying dynamical features and the role of stochasticity, we discuss the oscillatory dynamics in the well-studied regulatory network motif. The fluctuations around the fixed point of a delayed system are Gaussian in the limit of sufficiently weak delayed feedback, and remain Gaussian along a limit cycle when viewed tangential to the trajectory. The experimental results are recapitulated in this study. We illustrate several features of the p53 activities, which are robust when the parameters change. Furthermore, the distribution in protein abundance can be characterized by its non-Gaussian nature.     

Mass Detection of Single Viruses Based on Whispering Gallery Modes of Optomechanical Systems via Optical Pump–Probe Technique

Whispering gallery modes (WGMs), due to their high quality factors, small mode volumes and simple fabrications, have potential applications especially in sensing. In this work, we theoretically propose a mass sensor based on a realistic cavity optomechanical system (such as in Weis et al., Science 330, 1520 [2010]) in the presence of a strong pump laser and a weak probe laser. The mass of external bioparticles (such as smallpox virus and influenza virus) landing onto WGM cavity can be detected accurately via the probe transmission spectrum. Furthermore, based on this scheme one can even determine a single virus mass via monitoring the half-linewidth of the probe transmission spectrum. Through detecting the virus mass, one may identify the kinds of different viruses.