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A pair of new oxindole alkaloids, named macrophyllines C (1) and D (2), together with two known oxindole alkaloids isorhynchophylline (3) and corynoxine (4) were isolated from Uncaria macrophylla. Their structures were elucidated based on detailed spectroscopic analysis and by comparison with literature data. In addition, all the isolates were tested for their anti-HIV activities and cytotoxicities in C8166 cells and compounds 2–4 showed weak anti-HIV activities with EC50 values of 11.31 ± 3.29 μM, 18.77 ± 6.14 μM and 30.02 ± 3.73 μM, respectively. [ABSTRACT FROM AUTHOR]

The Chinese tree shrew ( Tupaia belangeri chinensis ), a member of the mammalian order Scandentia, exhibits considerable similarities with primates, including humans, in aspects of its nervous, immune, and metabolic systems. These similarities have established the tree shrew as a promising experimental model for biomedical research on cancer, infectious diseases, metabolic disorders, and mental health conditions. Herein, we used meta-transcriptomic sequencing to analyze plasma, as well as oral and anal swab samples, from 105 healthy asymptomatic tree shrews to identify the presence of potential zoonotic viruses. In total, eight mammalian viruses with complete genomes were identified, belonging to six viral families, including Flaviviridae , Hepeviridae , Parvovirinae , Picornaviridae , Sedoreoviridae , and Spinareoviridae . Notably, the presence of rotavirus was recorded in tree shrews for the first time. Three viruses - hepacivirus 1, parvovirus, and picornavirus - exhibited low genetic similarity (<70%) with previously reported viruses at the whole-genome scale, indicating novelty. Conversely, three other viruses - hepacivirus 2, hepatovirus A and hepevirus - exhibited high similarity (>94%) to known viral strains. Phylogenetic analyses also revealed that the rotavirus and mammalian orthoreovirus identified in this study may be novel reassortants. These findings provide insights into the diverse viral spectrum present in captive Chinese tree shrews, highlighting the necessity for further research into their potential for cross-species transmission.

The study of epidemics spreading with community structure has become a hot topic. The classic SIR epidemic model does not distinguish between dead and recovered individuals. It is inappropriate to classify dead individuals as recovered individuals because the real-world epidemic spread processes show different recovery rates and death rates in different communities. In the present work, a SIRD epidemic model with different recovery rates is proposed. We pay more attention to the changes in the number of dead individuals. The basic reproductive number is obtained. The stationary solutions of a disease-free state and an endemic state are given. We show that quarantining communities can decrease the basic reproductive number, and the total number of dead individuals decreases in a disease-free steady state with an increase in the number of quarantined communities. The most effective quarantining strategy is to preferentially quarantine some communities/cities with a greater population size and a fraction of initially infected individuals. Furthermore, we show that the population flows from a low recovery rate and high population density community/city/country to some high recovery rate and low population density communities/cities/countries, which helps to reduce the total number of dead individuals and prevent the prevalence of epidemics. The numerical simulations on the real-world network and the synthetic network further support our conclusions.

Multilayer networks are widely used to characterize the dynamic behavior of complex systems. The study of epidemic spreading dynamics on multilayer networks has become a hot topic in network science. Although many models have been proposed to explore epidemic spreading across different networks, there is still a lack of models to study the spreading of diseases in the process of evolution on multilayer homogeneous networks. In the present work, we propose an epidemic spreading dynamic model of homogeneous evolving networks that can be used to analyze and simulate the spreading of epidemics on such networks. We determine the global epidemic threshold. We make the interesting discovery that increasing the epidemic threshold of a single network layer is conducive to mitigating the spreading of an epidemic. We find that the initial average degree of a network and the evolutionary parameters determine the changes in the epidemic threshold and the spreading process. An approach for calculating the falling and rising threshold zones is presented. Our work provides a good strategy to control epidemic spreading. Generally, controlling or changing the threshold in a single network layer is easier than trying to directly change the threshold in all network layers. Numerical simulations of small-world and random networks further support and enrich our conclusions.