Angiotensin-converting enzyme 2(ACE2) is not only an enzyme but also a functional receptor on cell membrane for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Here, the activity of ACE2 in single living ...Angiotensin-converting enzyme 2(ACE2) is not only an enzyme but also a functional receptor on cell membrane for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Here, the activity of ACE2 in single living cell is firstly determined using a nanokit coupled electrospray ionization mass spectrometry(nanokit-ESI-MS). Upon the insertion of a micro-capillary into the living h ACE2-CHO cell and the electrochemical sorting of the cytosol, the target ACE2 enzyme hydrolyses angiotensin II inside the capillary to generate angiotensin 1-7. After the electrospray of the mixture at the tip of the capillary, the product is differentiated from the substrate in molecular weight to achieve the detection of ACE2 activity in single cells. The further measurement illustrates that the inflammatory state of cells does not lead to the significant change of ACE2 catalytic activity, which elucidates the relationship between intracellular ACE2 activity and inflammation at single cell level. The established strategy will provide a specific analytical method for further studying the role of ACE2 in the process of virus infection, and extend the application of nanokit based single cell analysis.展开更多
Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the predicti...Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the prediction of temporal patterns of influenza.Methods:We illustrate FDA methods using the weekly Influenza-like Illness(ILI)activity level data from the U.S.We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities.Functional analysis of variance(FANOVA)is used to examine the regional differences in temporal patterns and the impact of state's political orientation.Results:The ILI activity has a very distinct peak at the beginning and end of the year.There are significant differences in average level of ILI activities among geographic regions.However,the temporal patterns in terms of the peak and flat time are quite consistent across regions.The geographic and temporal patterns of ILI activities also depend on the political make-up of states.The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year.The influence of political party affiliation on temporal pattern is quite different among geographic regions.Conclusions:Functional data analysis can help us to reveal the temporal variability in average ILI levels,rate of change in ILI levels,and the effect of geographical regions.Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.展开更多
基金supported by Ministry of Science and Technology of China(No.2017YFA0700500)the National Natural Science Foundation of China(Nos.22025403 and 21974060)+1 种基金Kuanren Talents Program of the Second Affiliated Hospital of Chongqing Medical UniversityYoung and Middle-aged Senior Medical Talents Studio of Chongqing。
文摘Angiotensin-converting enzyme 2(ACE2) is not only an enzyme but also a functional receptor on cell membrane for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Here, the activity of ACE2 in single living cell is firstly determined using a nanokit coupled electrospray ionization mass spectrometry(nanokit-ESI-MS). Upon the insertion of a micro-capillary into the living h ACE2-CHO cell and the electrochemical sorting of the cytosol, the target ACE2 enzyme hydrolyses angiotensin II inside the capillary to generate angiotensin 1-7. After the electrospray of the mixture at the tip of the capillary, the product is differentiated from the substrate in molecular weight to achieve the detection of ACE2 activity in single cells. The further measurement illustrates that the inflammatory state of cells does not lead to the significant change of ACE2 catalytic activity, which elucidates the relationship between intracellular ACE2 activity and inflammation at single cell level. The established strategy will provide a specific analytical method for further studying the role of ACE2 in the process of virus infection, and extend the application of nanokit based single cell analysis.
基金Authors acknowledged the Canadian Institute for Health Research(CIHR)Children's Hospital Research Institute of Manitoba(CHRIM)Foundation+1 种基金Visual and Automated Disease Analytics(VADA)graduate training program of Natural Sciences and Engineering Research Council of Canada(NSERC)for providing the funding opportunities to conduct this research.
文摘Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the prediction of temporal patterns of influenza.Methods:We illustrate FDA methods using the weekly Influenza-like Illness(ILI)activity level data from the U.S.We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities.Functional analysis of variance(FANOVA)is used to examine the regional differences in temporal patterns and the impact of state's political orientation.Results:The ILI activity has a very distinct peak at the beginning and end of the year.There are significant differences in average level of ILI activities among geographic regions.However,the temporal patterns in terms of the peak and flat time are quite consistent across regions.The geographic and temporal patterns of ILI activities also depend on the political make-up of states.The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year.The influence of political party affiliation on temporal pattern is quite different among geographic regions.Conclusions:Functional data analysis can help us to reveal the temporal variability in average ILI levels,rate of change in ILI levels,and the effect of geographical regions.Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.
