Project description:Background: In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model. Methods: A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (Rc), as well as the effective daily reproduction ratio- Re(t), of the disease transmission in the mainland of China excluding Hubei province. Results: The estimation outcomes indicate that Rc is 3.36 (95% CI: 3.20-3.64) and Re(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020. Conclusions: To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

Project description:An extract prepared from species of Paris is the most widely consumed herbal product in China. The genus Paris includes a variety of genotypes with different medicinal component contents but only two are defined as official sources. Closely related species have different medicinal properties because of differential expression of proteins and metabolites. To better understand the molecular basis of these differences, we examined proteomic and metabolomic changes in rhizomes of P. polyphylla var. chinensis, P. polyphylla var. yunnanensis, and P. fargesii var. fargesii using a technique known as sequential window acquisition of all theoretical mass spectra as well as gas chromatography-time-of-flight mass spectrometry. In total, 419 proteins showed significant abundance changes, and 33 metabolites could be used to discriminate Paris species. A complex analysis of proteomic and metabolomic data revealed a higher efficiency of sucrose utilization and an elevated protein abundance in the sugar metabolic pathway of P. polyphylla var. chinensis. The pyruvate content and efficiency of acetyl-CoA-utilization in saponin biosynthesis were also higher in P. polyphylla var. chinensis than in the other two species. The results expand our understanding of the proteome and metabolome of Paris and offer new insights into the species-specific traits of these herbaceous plants.SIGNIFICANCE: The traditional Chinese medicine Paris is the most widely consumed herbal product for the treatment of joint pain, rheumatoid arthritis and antineoplastic. All Paris species have roughly the same morphological characteristics; however, different members have different medicinal compound contents. Efficient exploitation of genetic diversity is a key factor in the development of rare medicinal plants with improved agronomic traits and malleability to challenging environmental conditions. Nevertheless, only a partial understanding of physiological and molecular mechanisms of different plants of Paris can be achieved without proteomics. To better understand the molecular basis of these differences and facilitate the use of other Paris species, we examine proteomic metabolomic changes in rhizomes of Paris using the technique known as SWATH-MS and GC/TOF-MS. Our research has provided information that can be used in other studies to compare metabolic traits in different Paris species. Our findings can also serve as a theoretical basis for the selection and cultivation of other Paris species with a higher medicinal value.

Project description:Shigui Ruan. Modeling the transmission dynamics and control of rabies in China. Mathematical Biosciences 286 (2017). Human rabies was first recorded in ancient China in about 556 BC and is still one of the major public-health problems in China. From 1950 to 2015, 130,494 human rabies cases were reported in Mainland China with an average of 1977 cases per year. It is estimated that 95% of these human rabies cases are due to dog bites. The purpose of this article is to provide a review about the models, results, and simulations that we have obtained recently on studying the transmission of rabies in China. We first construct a basic susceptible, exposed, infectious, and recovered (SEIR) type model for the spread of rabies virus among dogs and from dogs to humans and use the model to simulate the human rabies data in China from 1996 to 2010. Then we modify the basic model by including both domestic and stray dogs and apply the model to simulate the human rabies data from Guangdong Province, China. To study the seasonality of rabies, in Section 4 we further propose a SEIR model with periodic transmission rates and employ the model to simulate the monthly data of human rabies cases reported by the Chinese Ministry of Health from January 2004 to December 2010. To understand the spatial spread of rabies, in Section 5 we add diffusion to the dog population in the basic SEIR model to obtain a reaction-diffusion equation model and determine the minimum wave speed connecting the disease-free equilibrium to the endemic equilibrium. Finally, in order to investigate how the movement of dogs affects the geographically inter-provincial spread of rabies in Mainland China, in Section 6 we propose a multi-patch model to describe the transmission dynamics of rabies between dogs and humans and use the two-patch submodel to investigate the rabies virus clades lineages and to simulate the human rabies data from Guizhou and Guangxi, Hebei and Fujian, and Sichuan and Shaanxi, respectively. Some discussions are provided in Section 7.

Project description:Tea plants (Camellia sinensis) present an excellent system to study evolution and diversification of specialized metabolites due to their abundance in classes, numbers and contents. A large number of tea cultivars have been cultivated throughout the world not only because of their adaption to different environments but of selection for specific flavors. The chemical and genetic basis for unique taste and aroma of different tea cultivars remains largely unknown, but is critical for guiding genetic breeding of new cultivars. Using transcriptomic data from 136 representative tea accessions in China, we obtain 925,854 high-quality single-nucleotide polymorphisms (SNPs) useful for marker-assisted breeding. Phylogenetic and population structure analyses separate sampled tea accessions into five major groups. Different major alleles are identified on 1183 SNP sites for the two major types of tea, C. sinensis var. assamica (CSA) and C. sinensis var. sinensis (CSS), reflecting fixation of these alleles after population divergence. Non-targeted metabolomic analyses detect 2,818 and 2,311 metabolic features in tea samples in positive and negative ionization modes, respectively, including 355 and 286 metabolites respectively that are differentially accumulated in different tea groups. Each phylogenetic group contains signature metabolites. In particular, CSA tea accessions are featured with high accumulation of diverse classes of flavonoid compounds, such as flavanols, flavonol mono-/di-glycosides and proanthocyanidin dimers. Comparisons of gene expression profiles of different tea groups identify hundreds of differentially expressed genes with some involved in the biosynthesis of characteristic tea metabolites, reflecting a combinational effect of genetic and environmental factors. Taken together, our study provides new insights into the phylogenetic relationships, molecular markers, metabolite compositions, and gene expression profiles of representative cultivated tea accessions in China, which are beneficial for targeted tea breeding and improvement.

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