A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,...A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.展开更多
目前网约车拼车服务存在响应不及时、乘客舒适度低等现象,亟需对拼车路线及求解算法进行优化。本文首先考虑路网条件及时间窗阈值影响,以网约车运行成本与乘客出行成本最小化为目标,构建基于双向线路的网约车拼车优化模型("one-to-...目前网约车拼车服务存在响应不及时、乘客舒适度低等现象,亟需对拼车路线及求解算法进行优化。本文首先考虑路网条件及时间窗阈值影响,以网约车运行成本与乘客出行成本最小化为目标,构建基于双向线路的网约车拼车优化模型("one-to-many"online car-hailing carpooling model under multiple constraints)。其次以遗传算法为基础,结合模拟退火温度调控机制,改进适应度评价和接受准则,提出混合遗传-模拟退火算法(hybrid genetic-simulated annealing algorithm,H-GASA)。最后以呼和浩特东站及其周围交通网络为例进行实例验证。实验结果表明,与其他算法相比,H-GASA算法在多种时间窗下均能有效降低乘客出行时间和车辆运营成本。此外,H-GASA算法得到的网约车拼车服务问题求解方案更优,收敛曲线更平缓,效率更高,验证了H-GASA在克服遗传算法过快收敛问题上的有效性。展开更多
基金supported by the National Natural Science Foundation of China(32273037 and 32102636)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030007)+4 种基金Laboratory of Lingnan Modern Agriculture Project(NT2021007)the Guangdong Science and Technology Innovation Leading Talent Program(2019TX05N098)the 111 Center(D20008)the double first-class discipline promotion project(2023B10564003)the Department of Education of Guangdong Province(2019KZDXM004 and 2019KCXTD001).
文摘A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.
文摘目前网约车拼车服务存在响应不及时、乘客舒适度低等现象,亟需对拼车路线及求解算法进行优化。本文首先考虑路网条件及时间窗阈值影响,以网约车运行成本与乘客出行成本最小化为目标,构建基于双向线路的网约车拼车优化模型("one-to-many"online car-hailing carpooling model under multiple constraints)。其次以遗传算法为基础,结合模拟退火温度调控机制,改进适应度评价和接受准则,提出混合遗传-模拟退火算法(hybrid genetic-simulated annealing algorithm,H-GASA)。最后以呼和浩特东站及其周围交通网络为例进行实例验证。实验结果表明,与其他算法相比,H-GASA算法在多种时间窗下均能有效降低乘客出行时间和车辆运营成本。此外,H-GASA算法得到的网约车拼车服务问题求解方案更优,收敛曲线更平缓,效率更高,验证了H-GASA在克服遗传算法过快收敛问题上的有效性。
