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	1. The circadian clock system in lung cancer
	Hou Xinzhu,Tao Shasha
	Preventive Medicine and Hygienics 12 May 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract:Lung cancer is the leading cause of cancer deaths worldwide. Despite the extensive characterization of events, which contribute to tumor initiation and progression, more and more recent studies forces on the relationship between circadian rhythm, like shift work and jet lag, and lung tumorigenesis. It is clear that the circadian clock system in lung is not only controlled by SCN, but also isolated from the SCN in some ways. There exists a negative and positive transcription/translation-based feedback loops in lung. Therefore, that the disorder of circadian clock system can lead to the risks of lung cancer has been described in multiple ways, including genes, cells, metabolism, immune function and inflammation processes and so on. This review emphasizes the important role of the circadian clock system in lung cancer, integrates the multiple relationship between circadian clock system and lung tumorigenesis, and hence puts forward new prospects in the prevention and cure of lung cancer.
	TO cite this article:Hou Xinzhu,Tao Shasha. The circadian clock system in lung cancer[OL].[12 May 2021] http://en.paper.edu.cn/en_releasepaper/content/4755035


	2. Accurate Simulations and Analysis of Xinfadi COVID-19 Epidemics in Beijing
	Min Lequan
	Preventive Medicine and Hygienics 19 December 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract: To date, more than 71 millions on infected with COVID-19 have been identified worldwide. It causes more 1.6 millions deaths and affects more than 200 countries and regions. Establishing a mathematical model for epidemic infectious diseases has played an important role in the formulation, evaluation, and prevention of control strategies. The event of Xinfadi COVID-19 epidemic provides a successful example for prevent and control strategies and clinical treatments. This paper introduces a symptomatic-asymptomatic-recoverer differential equation model (SARDE). It gives the conditions of the stability on the disease-free equilibrium of SARDE. It proposes the necessary conditions of disease spreading. It determines the parameters of SARDE based on the reported data of Xinfadi COVID-19 epidemic and simulations. Numerical simulations of SARDE describe well the outcomes of current symptomatic individuals, current asymptomatic but infected individuals, recovered symptomatic infected individuals, and recovered asymptomatic but infected individuals. The numerical simulations suggest that both symptomatic and asymptomatic individuals cause lesser asymptomatic spread than symptomatic spread; blocking rate of 97% cannot prevent the spread of Xinfadi COVID19 epidemic; the strict prevention and control strategies implemented by Beijing government are not only very effective but also completely necessary. It is expected that the research results can provide new theoretical tools and ideas worthy of reference for better understanding and dominating of epidemic spreads, preventions and controls.
	TO cite this article:Min Lequan. Accurate Simulations and Analysis of Xinfadi COVID-19 Epidemics in Beijing[OL].[19 December 2020] http://en.paper.edu.cn/en_releasepaper/content/4753222


	3. Simulations and Estimations of COVID-19 Epidemics in Beijing and Shanghai
	Min Lequan
	Preventive Medicine and Hygienics 27 July 2020
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	Abstract:The 2019 novel coronavirus (COVID-19) is a new virus that causes respiratory illness in people. This virus was first identified during an investigation into an outbreak in December 2019 Wuhan, China. To date, more than 15 millions on infected with COVID-19 have been identified worldwide. It causes more 600,000 deaths and affects more than 200 countries and regions. Establishing a mathematical model for epidemic infectious diseases has played an important role in the formulation,evaluation,and prevention of control strategies.This paper introduces such a model (INSIAR). This model improves one our previous mathematical model: susceptible-infected- asymptomatic-recoverer (NSIAR), and provides a subsidiary model (SM). SM can decribe the evolotions of cuumulative died, recovered infected and recovered asymptomatic individuals. Consequently INSIAR can provide more clear and detailed interpretations to the dynamics of COVID-19 epidemic than those done by NSIAR. The solutions of INSIAR are all positive and bounded. NSIAR has a disease-free equilibrium and a disease-persistent equilibrium. It provides criterions of local stability, and conditions of globally asymptotical stability on the disease-free equilibrium. It gives criterions of epidemic spread. As applications, utilizing the reported data of COVID-19 epidemics in Beijing and Shanghai (form the first infections discoveries to about two weeks\' after infectious peak points) , this paper determines the model parameters with different periods, simualtes and estimates the outmomes of the COVID-19 epidemics in Beijing and Shanghai, and evaluate the prevention of control strategies in Beijing and Shanghai. Simulation results are close to some repoted clinic data of the COVID-19 in Beijing and Shanghail. If Beijing would take group imunity or loose imunity measures for COVID-19 epidemics. Simulation results showed that in both cases, there were about 230000 death cases, and the end date of the loose imunity was not earlier than that of the group imunity. However, If the authority and people in Beijing keep the current strict prevention and control measures, a few outside input COVID-19 infectious cases will not generate epidemic spreading. The analysis suggest that Beijing and Shanghai have similar infecting and spreading patterns of COVID-19 epidemics. Both cites have implemented almost the same prevent and control measures. It is expected that the research results can provide new theoretical tools and ideas worthy of reference for better understanding and dominating of epidemic spreads, preventions and controls.
	TO cite this article:Min Lequan. Simulations and Estimations of COVID-19 Epidemics in Beijing and Shanghai[OL].[27 July 2020] http://en.paper.edu.cn/en_releasepaper/content/4752590


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