Structural modeling and dynamic evolution analysis of hypoxia response networks / 军事医学

Objective To construct an executable model of a hypoxia response network (HRN) and to analyze the dynamic evolution mechanism of an HRN including randomness as well as concurrency based on computer simulation. Methods Specific evolution rules and Gillespie algorithm were adoped to study the dynamic evolution of the structural model based on the construction of a structural model of an HRN using stochastic Petri net ( SPN ) .Results Dynamic evolution laws of an HRN were obtained and the simulation results were consistent with laboratory results in response to descript switch-like behavior of an HRN .Conclusion A visualization model of the HRN can be achieved using SPN method.Simulation results achieved by executing the model based on stochastic simulation using specific kinetic parameters can serve as a nice complement to traditional laboratory results , which can help shed light on the structure and function characteristics of an HRN.

Lessons Learned from International Responses to Severe Acute Respiratory Syndrome (SARS)

In early February 2003, a previously unknown disease causing severe pneumonia was recognised. This disease which is now known as severe acute respiratory syndrome (SARS) is believed to have had its origins in the Guangdong Province of China, and was the cause of a multi-country epidemic resulting in significant morbidity and mortality. The World Health Organization (WHO) has been coordinating the international response to provide the epidemiological, laboratory, clinical and logistic requirements needed to contain this disease. A rapid spread of SARS around the world occurred at its onset, facilitated greatly by air travel. Between November 2002 and July 2003, a total of 8,094 cases and 774 cases were reported from 26 countries worldwide. WHO responded quickly to this multi-country outbreak and on 12 March released a “global alert” about SARS. This was followed by the first WHO travel advisory on 15 March. The Global Outbreak Alert and Response Network was activated, and international experts were brought together to implement enhanced global surveillance systems for SARS. The international community has learned a lot of lessons from the SARS outbreak. Particularly, rapid and transparent information sharing between countries is critical to prevent international spread of the disease. However, information exchange was less than optimal in the early phase of the outbreak.

Lessons learned from international responses to severe acute respiratory syndrome (SARS)

In early February 2003, a previously unknown disease causing severe pneumonia was recognised. This disease which is now known as severe acute respiratory syndrome (SARS) is believed to have had its origins in the Guangdong Province of China, and was the cause of a multi-country epidemic resulting in significant morbidity and mortality. The World Health Organization (WHO) has been coordinating the international response to provide the epidemiological, laboratory, clinical and logistic requirements needed to contain this disease.A rapid spread of SARS around the world occurred at its onset, facilitated greatly by air travel. Between November 2002 and July 2003, a total of 8,094 cases and 774 cases were reported from 26 countries worldwide.WHO responded quickly to this multi-country outbreak and on 12 March released a "global alert" about SARS. This was followed by the first WHO travel advisory on 15 March. The Global Outbreak Alert and Response Network was activated, and international experts were brought together to implement enhanced global surveillance systems for SARS.The international community has learned a lot of lessons from the SARS outbreak. Particularly, rapid and transparent information sharing between countries is critical to prevent international spread of the disease. However, information exchange was less than optimal in the early phase of the outbreak.