A sandwich format immunochromatographic assay for detecting foot-and-mouth disease virus (FMDV) serotypes was developed. In this rapid test,affinity purified polyclonal antibodies from Guinea pigs which were immunized...A sandwich format immunochromatographic assay for detecting foot-and-mouth disease virus (FMDV) serotypes was developed. In this rapid test,affinity purified polyclonal antibodies from Guinea pigs which were immunized with sucking-mouse adapted FMD virus (A/AV88(L) strain) were conjugated to colloidal gold beads and used as the capture antibody,and affinity purified polyclonal antibodies from rabbits which were immunized with cell-culture adapted FMD virus (A/CHA/09 strain) were used as detector antibody. On the nitrocellulose membrane of the immunochromatographic strip,the capture antibody was laid on a sample pad,the detector antibody was printed at the test line(T) and goat anti-guinea pigs IgG antibodies were immobilized to the control line(C). The lower detection limit of the test for a FMDV 146S antigen is 11.7ng/ml as determined in serial tests after the strip device was assembled and the assay condition optimization. No cross reactions were found with FMDV serotype C,Swine vesicular disease (SVD),Vesicular stomatiti svirus (VSV) and vesicular exanthema of swine virus (VES) viral antigens with this rapid test. Clinically,the diagnostic sensitivity of this test for FMDV serotypes A was 88.7% which is as same as an indirect-sandwich ELISA. The specificity of this strip test was 98.2% and is comparable to the 98.7% obtained with indirect-sandwich ELISA. This rapid strip test is simple,easy and fast for clinical testing on field sites; no special instruments and skills are required,and the result can be obtained within 15 min. To our knowledge,this is the first rapid immunochromatogarpic assay for serotype A of FMDV.展开更多
提出了一种快速判别交通流混沌的最大Lyapunov指数改进算法.该算法首先用关联积分法(C-C方法)和C ao方法确定重构相空间的两个重要参数:嵌入维数m和延迟时间,再用小数据量方法计算时间序列的最大Lyapunov指数.这种算法不仅能够很好地重...提出了一种快速判别交通流混沌的最大Lyapunov指数改进算法.该算法首先用关联积分法(C-C方法)和C ao方法确定重构相空间的两个重要参数:嵌入维数m和延迟时间,再用小数据量方法计算时间序列的最大Lyapunov指数.这种算法不仅能够很好地重构原始时间序列的特性,并且能够避免W o lf方法的局限性.应用最大Lyapunov指数改进算法对仿真交通流和实测交通流的时间序列进行了混沌判别,结果表明,基于跟驰模型的仿真交通流和实际交通流中存在混沌现象,最大Lyapunov指数改进算法是准确判定时间序列是否具有混沌特性的一种有效方法.展开更多
基金Financial supported by the Gansu ProvincialSci. & Tech. Department (1002NKDA037)
文摘A sandwich format immunochromatographic assay for detecting foot-and-mouth disease virus (FMDV) serotypes was developed. In this rapid test,affinity purified polyclonal antibodies from Guinea pigs which were immunized with sucking-mouse adapted FMD virus (A/AV88(L) strain) were conjugated to colloidal gold beads and used as the capture antibody,and affinity purified polyclonal antibodies from rabbits which were immunized with cell-culture adapted FMD virus (A/CHA/09 strain) were used as detector antibody. On the nitrocellulose membrane of the immunochromatographic strip,the capture antibody was laid on a sample pad,the detector antibody was printed at the test line(T) and goat anti-guinea pigs IgG antibodies were immobilized to the control line(C). The lower detection limit of the test for a FMDV 146S antigen is 11.7ng/ml as determined in serial tests after the strip device was assembled and the assay condition optimization. No cross reactions were found with FMDV serotype C,Swine vesicular disease (SVD),Vesicular stomatiti svirus (VSV) and vesicular exanthema of swine virus (VES) viral antigens with this rapid test. Clinically,the diagnostic sensitivity of this test for FMDV serotypes A was 88.7% which is as same as an indirect-sandwich ELISA. The specificity of this strip test was 98.2% and is comparable to the 98.7% obtained with indirect-sandwich ELISA. This rapid strip test is simple,easy and fast for clinical testing on field sites; no special instruments and skills are required,and the result can be obtained within 15 min. To our knowledge,this is the first rapid immunochromatogarpic assay for serotype A of FMDV.
文摘提出了一种快速判别交通流混沌的最大Lyapunov指数改进算法.该算法首先用关联积分法(C-C方法)和C ao方法确定重构相空间的两个重要参数:嵌入维数m和延迟时间,再用小数据量方法计算时间序列的最大Lyapunov指数.这种算法不仅能够很好地重构原始时间序列的特性,并且能够避免W o lf方法的局限性.应用最大Lyapunov指数改进算法对仿真交通流和实测交通流的时间序列进行了混沌判别,结果表明,基于跟驰模型的仿真交通流和实际交通流中存在混沌现象,最大Lyapunov指数改进算法是准确判定时间序列是否具有混沌特性的一种有效方法.
