Information-epidemic co-evolution propagation under policy intervention in multiplex networks.

The emergence of epidemics has seriously threatened the running of human society, such as COVID-19. During the epidemics, some external factors usually have a non-negligible impact on the epidemic transmission. Therefore, we not only consider the interaction between epidemic-related information and infectious diseases, but also the influence of policy interventions on epidemic propagation in this work. We establish a novel model that includes two dynamic processes to explore the co-evolutionary spread of epidemic-related information and infectious diseases under policy intervention, one of which depicts information diffusion about infectious diseases and the other denotes the epidemic transmission. A weighted network is introduced into the epidemic spreading to characterize the impact of policy interventions on social distance between individuals. The dynamic equations are established to describe the proposed model according to the micro-Markov chain (MMC) method. The derived analytical expressions of the epidemic threshold indicate that the network topology, epidemic-related information diffusion and policy intervention all have a direct impact on the epidemic threshold. We use numerical simulation experiments to verify the dynamic equations and epidemic threshold, and further discuss the co-evolution dynamics of the proposed model. Our results show that strengthening epidemic-related information diffusion and policy intervention can significantly inhibit the outbreak and spread of infectious diseases. The current work can provide some valuable references for public health departments to formulate the epidemic prevention and control measures.

Diastereoselective Synthesis of Tetracyclic Tetrahydroquinoline Derivative Enabled by Multicomponent Reaction of Isocyanide, Allenoate, and 2-Aminochalcone.

We report here a multicomponent protocol to assemble several polycyclic dihydropyran-fused tetrahydroquinoline structures with excellent diastereoselectivity. This procedure employs simple feedstocks to accomplish a series of diverse structures, which is difficult to attain by traditional sequences.

Epidemic Propagation With Positive and Negative Preventive Information in Multiplex Networks.

We propose a novel epidemic model based on two-layered multiplex networks to explore the influence of positive and negative preventive information on epidemic propagation. In the model, one layer represents a social network with positive and negative preventive information spreading competitively, while the other one denotes the physical contact network with epidemic propagation. The individuals who are aware of positive prevention will take more effective measures to avoid being infected than those who are aware of negative prevention. Taking the microscopic Markov chain (MMC) approach, we analytically derive the expression of the epidemic threshold for the proposed epidemic model, which indicates that the diffusion of positive and negative prevention information, as well as the topology of the physical contact network have a significant impact on the epidemic threshold. By comparing the results obtained with MMC and those with the Monte Carlo (MC) simulations, it is found that they are in good agreement, but MMC can well describe the dynamics of the proposed model. Meanwhile, through extensive simulations, we demonstrate the impact of positive and negative preventive information on the epidemic threshold, as well as the prevalence of infectious diseases. We also find that the epidemic prevalence and the epidemic outbreaks can be suppressed by the diffusion of positive preventive information and be promoted by the diffusion of negative preventive information.

Co-evolution spreading of multiple information and epidemics on two-layered networks under the influence of mass media.

During epidemic outbreaks, there are various types of information about epidemic prevention disseminated simultaneously among the population. Meanwhile, the mass media also scrambles to report the information related to the epidemic. Inspired by these phenomena, we devise a model to discuss the dynamical characteristics of the co-evolution spreading of multiple information and epidemic under the influence of mass media. We construct the co-evolution model under the framework of two-layered networks and gain the dynamical equations and epidemic critical point with the help of the micro-Markov chain approach. The expression of epidemic critical point show that the positive and negative information have a direct impact on the epidemic critical point. Moreover, the mass media can indirectly affect the epidemic size and epidemic critical point through their interference with the dissemination of epidemic-relevant information. Though extensive numerical experiments, we examine the accuracy of the dynamical equations and expression of the epidemic critical point, showing that the dynamical characteristics of co-evolution spreading can be well described by the dynamic equations and the epidemic critical point is able to be accurately calculated by the derived expression. The experimental results demonstrate that accelerating positive information dissemination and enhancing the propaganda intensity of mass media can efficaciously restrain the epidemic spreading. Interestingly, the way to accelerate the dissemination of negative information can also alleviate the epidemic to a certain extent when the positive information hardly spreads. Current results can provide some useful clues for epidemic prevention and control on the basis of epidemic-relevant information dissemination.

Cascade cyclization and acyl migration of propargylic esters with isocyanides: rapid access to substituted furans.

A novel rearrangement of ester-activated propargylic acetate with isocyanide has been disclosed. This protocol enables a quick synthesis of polysubstituted furan derivatives. The reaction outcome also reveals that the ester group is employed for the construction of a furan ring and an acyl migration is observed.

[Effects on Salvia miltiorrhiza hairy roots of tanshinones content accumulation after treated with fosmidomycin].

Fosmidomycin (100 micromol x L(-1)) which is the effective inhibitor of DXR, key enzyme in terpenoid MEP pathway, was used to treat with hairy roots of Salvia miltiorrhiza. The treated roots were harvested at 2, 4, 6, 8, 10, 16 and 21 d, mRNA level of SmDXR and tanshinone content in treated and negative control groups were detected. Results found that, after treated with fosmidomycin, color of S. miltiorrhiza hairy roots grew pale gradually comparing with controls; mRNA level of SmDXR in hairy roots varied as a shape of parabolic and the highest value achieved at the sixth day after treatment, then it decreased gradually; Content of four kinds of tanshinones were detected. Among of the four kinds of tanshinones, Tanshinone I content changed relatively little, while content of dihydrotanshinone I, cryptotanshinone and tanshinone II (A) decreased gradually in 21 days. The content of total tanshinones in NC groups was 5, 63 times more than FOS-treated roots in the 21th day. The previous results showed that SmDXR played an important role in the accumulation of tanshinone content in MEP pathway. Once the mRNA level of SmDXR was suppressed, the accumulation of secondary metabolites will be significantly affected.