African swine fever(ASF)is a devastating infectious disease in swine that is severely threatening the global pig industry.An efficacious vaccine is urgently required.Here,we used the Chinese ASFV HLJ/18 as a backbone ...African swine fever(ASF)is a devastating infectious disease in swine that is severely threatening the global pig industry.An efficacious vaccine is urgently required.Here,we used the Chinese ASFV HLJ/18 as a backbone and generated a series of genedeleted viruses.The virulence,immunogenicity,safety,and protective efficacy evaluation in specific-pathogen-free pigs,commercial pigs,and pregnant sows indicated that one virus,namely HLJ/18-7GD,which has seven genes deleted,is fully attenuated in pigs,cannot convert to the virulent strain,and provides complete protection of pigs against lethal ASFV challenge.Our study shows that HLJ/-18-7GD is a safe and effective vaccine against ASFV,and as such is expected to play an important role in controlling the spread of ASFV.展开更多
Risk prediction tools are crucial for population-based management of cardiovascular disease(CVD).However,most prediction models are currently used to assess long-term risk instead of the risk of short-term CVD onset.W...Risk prediction tools are crucial for population-based management of cardiovascular disease(CVD).However,most prediction models are currently used to assess long-term risk instead of the risk of short-term CVD onset.We developed a Dynamic Risk-based Early wAming Monitoring(DREAM)system using large-scale,real-time electronic health record data from 2010 to 2020 from the CHinese Electronic health Records Research in Yinzhou study.The dynamic risk scores were derived from a 1:5 matched nested case-control set comprising 70,470 individuals(11,745 CVD events)and then validated in a cohort of 81,205 individuals(5950 CVD events).The individuals were Chinese adults aged 40-79 years without a history of CVD at baseline.Eleven predictors related to vital signs,laboratory tests,and health service utilization were selected to establish the dynamic scores.The proposed scores were significantly associated with the subsequent CVD onset(adjusted odds ratio,1.21;95%confidence interval,1.20-1.23).The area under the receiver operating characteristic curves(AUCs)was 0.6010(0.5929-0.6092)and 0.6021(0.5937-0.6105)for the long-term 10-year CVD risk<10%and≥10%groups in the derivation set,respectively.In the long-term 10-year CVD risk>10%group in the validation set,the change in AUC in addition to the long-term risk was 0.0235(0.0155-0.0315).By increasing the risk threshold from 7 to 16 points,the proportion of true subsequent CVD cases among those given alerts increased from 40.61%to 85.31%.In terms of management efficiency,the number needed to manage per CVD case ranged from 2.46 to 1.17 using the risk scores.With the increasing popularity and integration of EHR systems with wearable technology,the DREAM scores can be incorporated into an early-warning system and applied in dynamic,real-time,EHR-based,automated management to support healthcare decision making for individuals,general practitioners,and policymakers.展开更多
基金supported by the National Key R&D Program of China(2018YFC1200601)Applied Technology Research and Development Project of Heilongjiang Province(GA19B301)+1 种基金Key-Area Research and Development Program of Guangdong Province(2019B020211004)the grant from the State Key Laboratory of Veterinary Biotechnology Program(SKLVBP201801)。
文摘African swine fever(ASF)is a devastating infectious disease in swine that is severely threatening the global pig industry.An efficacious vaccine is urgently required.Here,we used the Chinese ASFV HLJ/18 as a backbone and generated a series of genedeleted viruses.The virulence,immunogenicity,safety,and protective efficacy evaluation in specific-pathogen-free pigs,commercial pigs,and pregnant sows indicated that one virus,namely HLJ/18-7GD,which has seven genes deleted,is fully attenuated in pigs,cannot convert to the virulent strain,and provides complete protection of pigs against lethal ASFV challenge.Our study shows that HLJ/-18-7GD is a safe and effective vaccine against ASFV,and as such is expected to play an important role in controlling the spread of ASFV.
基金supported by the National Natural Science Foundation of China[Grant No.91846112,81973132,81961128006]the Chinese Ministry of Science and Technology[Grant No.2020YFC2003503].
文摘Risk prediction tools are crucial for population-based management of cardiovascular disease(CVD).However,most prediction models are currently used to assess long-term risk instead of the risk of short-term CVD onset.We developed a Dynamic Risk-based Early wAming Monitoring(DREAM)system using large-scale,real-time electronic health record data from 2010 to 2020 from the CHinese Electronic health Records Research in Yinzhou study.The dynamic risk scores were derived from a 1:5 matched nested case-control set comprising 70,470 individuals(11,745 CVD events)and then validated in a cohort of 81,205 individuals(5950 CVD events).The individuals were Chinese adults aged 40-79 years without a history of CVD at baseline.Eleven predictors related to vital signs,laboratory tests,and health service utilization were selected to establish the dynamic scores.The proposed scores were significantly associated with the subsequent CVD onset(adjusted odds ratio,1.21;95%confidence interval,1.20-1.23).The area under the receiver operating characteristic curves(AUCs)was 0.6010(0.5929-0.6092)and 0.6021(0.5937-0.6105)for the long-term 10-year CVD risk<10%and≥10%groups in the derivation set,respectively.In the long-term 10-year CVD risk>10%group in the validation set,the change in AUC in addition to the long-term risk was 0.0235(0.0155-0.0315).By increasing the risk threshold from 7 to 16 points,the proportion of true subsequent CVD cases among those given alerts increased from 40.61%to 85.31%.In terms of management efficiency,the number needed to manage per CVD case ranged from 2.46 to 1.17 using the risk scores.With the increasing popularity and integration of EHR systems with wearable technology,the DREAM scores can be incorporated into an early-warning system and applied in dynamic,real-time,EHR-based,automated management to support healthcare decision making for individuals,general practitioners,and policymakers.