Modelling the impact of human behavior using a two-layer Watts-Strogatz network for transmission and control of Mpox.

PURPOSE: This study aims to evaluate the effectiveness of mitigation strategies and analyze the impact of human behavior on the transmission of Mpox. The results can provide guidance to public health authorities on comprehensive prevention and control for the new Mpox virus strain in the Democratic Republic of Congo as of December 2023. METHODS: We develop a two-layer Watts-Strogatz network model. The basic reproduction number is calculated using the next-generation matrix approach. Markov chain Monte Carlo (MCMC) optimization algorithm is used to fit Mpox cases in Canada into the network model. Numerical simulations are used to assess the impact of mitigation strategies and human behavior on the final epidemic size. RESULTS: Our results show that the contact transmission rate of low-risk groups and susceptible humans increases when the contact transmission rate of high-risk groups and susceptible humans is controlled as the Mpox epidemic spreads. The contact transmission rate of high-risk groups after May 18, 2022, is approximately 20% lower than that before May 18, 2022. Our findings indicate a positive correlation between the basic reproduction number and the level of heterogeneity in human contacts, with the basic reproduction number estimated at 2.3475 (95% CI: 0.0749-6.9084). Reducing the average number of sexual contacts to two per week effectively reduces the reproduction number to below one. CONCLUSION: We need to pay attention to the re-emergence of the epidemics caused by low-risk groups when an outbreak dominated by high-risk groups is under control. Numerical simulations show that reducing the average number of sexual contacts to two per week is effective in slowing down the rapid spread of the epidemic. Our findings offer guidance for the public health authorities of the Democratic Republic of Congo in developing effective mitigation strategies.

Non-targeted metabolomics reveals the characteristics of the unique bitterness substances in quinoa.

Bitterness is a key factor that affects the consumption of quinoa products, even if they are nutritious. In this study, a non-targeted metabolomics approach based on UHPLC-Orbitrap-MS was applied to comprehensively profile the characteristic metabolites of twenty-two quinoas. A total of twenty key metabolites were identified correlated with bitterness, among which, fifteen were triterpenoid saponins. In addition, these metabolites bind to the active site of the human bitter taste receptor and are the main compounds that produce the bitter taste of quinoa. Our results contribute to a deeper understanding of the origin of quinoa bitterness and provide directions for optimizing its flavor to improve market acceptance.

Spatio-temporal characteristics and influencing factors of urban shrinkage in county level of Heilongjiang Province, Northeast China.

Urban shrinkage has become increasingly prevalent in the context of global urbanization. Understanding its spatio-temporal characteristics and influencing factors is of great significance for promoting sustainable development and high-quality urbanization. This paper identified county-level shrinking cities in Heilongjiang Province from the perspective of urban entities. It employed spatial autocorrelation methods to analyze their spatial-temporal characteristics and explored the factors that contributed to this phenomenon. The results indicated that between 2010 and 2020, the phenomenon of urban shrinkage at the county level in Heilongjiang Province was primarily concentrated in the province's hinterland. Moreover, they exhibited characteristics of the Great Recession and Small Growth. The main factors influencing the shrinkage included the urban industrial structure, living standards, and population composition.