目的探讨应用彩色多普勒超声血流检测及生物物理评分(BPS)诊断胎儿宫内缺氧的价值。方法将2015年3月至2017年3月宝鸡市中医医院妇产科收治的60例胎儿宫内窘迫孕妇为研究组,并选择60例正常孕妇为对照组,均采用彩色多普勒超声检测大脑中动...目的探讨应用彩色多普勒超声血流检测及生物物理评分(BPS)诊断胎儿宫内缺氧的价值。方法将2015年3月至2017年3月宝鸡市中医医院妇产科收治的60例胎儿宫内窘迫孕妇为研究组,并选择60例正常孕妇为对照组,均采用彩色多普勒超声检测大脑中动脉(MCA)、静脉导管(DV)、脐动脉(UA)血流指数,采用B超获得胎儿BPS评分,比较两组孕妇MCA、DV、UA血流指数和BPS评分的差异,并分析超声血流检测、BPS、联合检测诊断胎儿宫内窘迫的价值。结果研究组孕妇BPS评分低于对照组[(4.02±1.92)分vs (6.32±2.59)分],MCAPI、MCAR1、MCAS/D低于对照组[(1.12±0.23) vs (1.85±0.45)、(0.63±0.04) vs (0.79±0.06)、(3.02±0.25) vs (4.97±0.28)],UAPI、UARI、UAS/D、DVPIV、DVPVIV高于对照组[(1.28±0.26) vs (0.81±0.21)、(0.76±0.09) vs (0.52±0.03)、(4.03±0.18) vss (2.06±0.22)、(0.85±0.03) vs (0.60±0.03)、(0.78±0.06) vs (0.50±0.04)],差异均有统计学意义(P<0.05);研究组孕妇BPS、超声血流检测胎儿宫内窘迫的阳性率高于对照组[58.33%vs 20.00%、70.00%vs 25.00%],差异均有统计学意义(P<0.05);研究组联合检测阳性率为88.33%,高于BPS单独检测的58.33%和超声血流检测的70.00%,差异均有统计学意义(P<0.05)。BPS、超声血流检测、联合检测诊断胎儿宫内窘迫的曲线下面积(AUC)分别为0.761 (95%CI:0.364～0.951)、0.803 (95%CI:0.271～0.806)、0.902 (95%CI:0.135～0.947),灵敏度和特异度分别为73.16%、54.61%;81.64%、71.52%;92.34%、95.37%。结论彩色多普勒超声血流检测诊断胎儿宫内窘迫的价值高于生物物理评分,联合检测可提高胎儿宫内窘迫的诊断价值。展开更多
Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles （PSP） have been introduced as important characteristics of proteins in this article. In this study, to obtain...Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles （PSP） have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific lterative-Basic Local Alignment Search Tool （PSI-BLAST） has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and lst-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network （PSP-WNN）. The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.展开更多
文摘目的探讨应用彩色多普勒超声血流检测及生物物理评分(BPS)诊断胎儿宫内缺氧的价值。方法将2015年3月至2017年3月宝鸡市中医医院妇产科收治的60例胎儿宫内窘迫孕妇为研究组,并选择60例正常孕妇为对照组,均采用彩色多普勒超声检测大脑中动脉(MCA)、静脉导管(DV)、脐动脉(UA)血流指数,采用B超获得胎儿BPS评分,比较两组孕妇MCA、DV、UA血流指数和BPS评分的差异,并分析超声血流检测、BPS、联合检测诊断胎儿宫内窘迫的价值。结果研究组孕妇BPS评分低于对照组[(4.02±1.92)分vs (6.32±2.59)分],MCAPI、MCAR1、MCAS/D低于对照组[(1.12±0.23) vs (1.85±0.45)、(0.63±0.04) vs (0.79±0.06)、(3.02±0.25) vs (4.97±0.28)],UAPI、UARI、UAS/D、DVPIV、DVPVIV高于对照组[(1.28±0.26) vs (0.81±0.21)、(0.76±0.09) vs (0.52±0.03)、(4.03±0.18) vss (2.06±0.22)、(0.85±0.03) vs (0.60±0.03)、(0.78±0.06) vs (0.50±0.04)],差异均有统计学意义(P<0.05);研究组孕妇BPS、超声血流检测胎儿宫内窘迫的阳性率高于对照组[58.33%vs 20.00%、70.00%vs 25.00%],差异均有统计学意义(P<0.05);研究组联合检测阳性率为88.33%,高于BPS单独检测的58.33%和超声血流检测的70.00%,差异均有统计学意义(P<0.05)。BPS、超声血流检测、联合检测诊断胎儿宫内窘迫的曲线下面积(AUC)分别为0.761 (95%CI:0.364～0.951)、0.803 (95%CI:0.271～0.806)、0.902 (95%CI:0.135～0.947),灵敏度和特异度分别为73.16%、54.61%;81.64%、71.52%;92.34%、95.37%。结论彩色多普勒超声血流检测诊断胎儿宫内窘迫的价值高于生物物理评分,联合检测可提高胎儿宫内窘迫的诊断价值。
基金the National Natural Science Foundation of China (No. 60471003).
文摘Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles （PSP） have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific lterative-Basic Local Alignment Search Tool （PSI-BLAST） has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and lst-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network （PSP-WNN）. The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.
