目的探究血清叉头盒蛋白M1(forkhead box protein M1,FOXM1)和胰岛素样生长因子2(insulin-like growth factor 2,IGF2)表达对老年心力衰竭合并肺炎患者预后的预测价值。方法将邯郸市中心医院2021年3月~2022年6月收治的126例老年心力衰...目的探究血清叉头盒蛋白M1(forkhead box protein M1,FOXM1)和胰岛素样生长因子2(insulin-like growth factor 2,IGF2)表达对老年心力衰竭合并肺炎患者预后的预测价值。方法将邯郸市中心医院2021年3月~2022年6月收治的126例老年心力衰竭并发肺炎患者设为病例组,并根据随访情况将122例患者分为预后不良组(n=33)和预后良好组(n=89),另选取该院同期126例健康体检者为对照组。检测两组(病例组和对照组)血清FOXM1和IGF2水平,检测病例组用力肺活量(forced vital capacity,FVC)和第一秒用力呼容积(forced expiratory volume in one second,FEV1)。采用Spearman分析法分析老年心力衰竭并发肺炎患者血清FOXM1和IGF2水平与心功能分级的相关性;受试者工作特征(receiver operating characteristic,ROC)曲线分析血清FOXM1和IGF2水平对老年心力衰竭并发肺炎患者预后的预测价值。结果与对照组比较,病例组血清FOXM1(2.39±0.55 vs 1.06±0.21)和IGF2(71.33±7.96pg/ml vs 47.82±5.14pg/ml)水平明显较高,差异有统计学意义(t=25.358,27.581,均P<0.05);与预后良好组比较,预后不良组血清FOXM1(3.87±1.06 vs 1.95±0.51)和IGF2水平(85.88±9.54pg/ml vs 69.14±8.73pg/ml)明显较高,差异具有统计学意义(t=13.453,9.174,均P<0.05);预后良好组和预后不良组心功能分级比较差异有统计学意义(χ^(2)=7.120,P<0.05),且与预后不良组比较,预后良好组FEV1(1.24±0.32L vs 1.08±0.25L)和FEV1/FVC(55.46%±5.77%vs 52.30%±5.38%)明显较高,差异有统计学意义(t=2.592,2.735,均P<0.05);老年心力衰竭并发肺炎患者血清FOXM1水平和IGF2水平与心功能分级呈显著正相关(r=0.496,0.517,均P<0.05)。ROC曲线结果显示,血清FOXM1单独预测老年心力衰竭并发肺炎患者预后的曲线下面积(area under the curve,AUC)为0.854(95CI%:0.779~0.912),其敏感度、特异度分别为75.76%,86.52%,最佳截断值为2.75;IGF2单独预测老年心力衰竭并发肺炎患者预后的AUC为0.874(95CI%:0.802~0.927),其敏感度、特异度分别为72.73%,85.39%,最佳截断值为78.30 pg/ml;二者联合预测老年心力衰竭并发肺炎患者预后的AUC显著大于血清FOXM1和IGF2单独诊断的AUC(Z=2.413,2.737,P=0.006,0.016)。结论血清FOXM1和IGF2水平在老年心力衰竭并发肺炎患者中升高,且二者联合检测对患者预后具有较高的预测价值。展开更多
Formal verification is fundamental in many phases of digital systems design. The most successful verification procedures employ Ordered Binary Decision Diagrams (OBDDs) as canonical representation for both Boolean cir...Formal verification is fundamental in many phases of digital systems design. The most successful verification procedures employ Ordered Binary Decision Diagrams (OBDDs) as canonical representation for both Boolean circuit specifications and logic designs, but these methods require a large amount of memory and time. Due to these limitations, several models of Decision Diagrams have been studied and other verification techniques have been proposed. In this paper, we have used probabilistic verification with Galois (or finite) field GF(2m) modifying the CUDD package for the computation of signatures in classical OBDDs, and for the construction of Mod2-OBDDs (also known as ?-OBDDs). Mod2-OBDDs have been constructed with a two-level layer of ?-nodes using a positive Davio expansion (pDE) for a given variable. The sizes of the Mod2-OBDDs obtained with our method are lower than the Mod2-OBDDs sizes obtained with other similar methods.展开更多
文摘目的探究血清叉头盒蛋白M1(forkhead box protein M1,FOXM1)和胰岛素样生长因子2(insulin-like growth factor 2,IGF2)表达对老年心力衰竭合并肺炎患者预后的预测价值。方法将邯郸市中心医院2021年3月~2022年6月收治的126例老年心力衰竭并发肺炎患者设为病例组,并根据随访情况将122例患者分为预后不良组(n=33)和预后良好组(n=89),另选取该院同期126例健康体检者为对照组。检测两组(病例组和对照组)血清FOXM1和IGF2水平,检测病例组用力肺活量(forced vital capacity,FVC)和第一秒用力呼容积(forced expiratory volume in one second,FEV1)。采用Spearman分析法分析老年心力衰竭并发肺炎患者血清FOXM1和IGF2水平与心功能分级的相关性;受试者工作特征(receiver operating characteristic,ROC)曲线分析血清FOXM1和IGF2水平对老年心力衰竭并发肺炎患者预后的预测价值。结果与对照组比较,病例组血清FOXM1(2.39±0.55 vs 1.06±0.21)和IGF2(71.33±7.96pg/ml vs 47.82±5.14pg/ml)水平明显较高,差异有统计学意义(t=25.358,27.581,均P<0.05);与预后良好组比较,预后不良组血清FOXM1(3.87±1.06 vs 1.95±0.51)和IGF2水平(85.88±9.54pg/ml vs 69.14±8.73pg/ml)明显较高,差异具有统计学意义(t=13.453,9.174,均P<0.05);预后良好组和预后不良组心功能分级比较差异有统计学意义(χ^(2)=7.120,P<0.05),且与预后不良组比较,预后良好组FEV1(1.24±0.32L vs 1.08±0.25L)和FEV1/FVC(55.46%±5.77%vs 52.30%±5.38%)明显较高,差异有统计学意义(t=2.592,2.735,均P<0.05);老年心力衰竭并发肺炎患者血清FOXM1水平和IGF2水平与心功能分级呈显著正相关(r=0.496,0.517,均P<0.05)。ROC曲线结果显示,血清FOXM1单独预测老年心力衰竭并发肺炎患者预后的曲线下面积(area under the curve,AUC)为0.854(95CI%:0.779~0.912),其敏感度、特异度分别为75.76%,86.52%,最佳截断值为2.75;IGF2单独预测老年心力衰竭并发肺炎患者预后的AUC为0.874(95CI%:0.802~0.927),其敏感度、特异度分别为72.73%,85.39%,最佳截断值为78.30 pg/ml;二者联合预测老年心力衰竭并发肺炎患者预后的AUC显著大于血清FOXM1和IGF2单独诊断的AUC(Z=2.413,2.737,P=0.006,0.016)。结论血清FOXM1和IGF2水平在老年心力衰竭并发肺炎患者中升高,且二者联合检测对患者预后具有较高的预测价值。
文摘Formal verification is fundamental in many phases of digital systems design. The most successful verification procedures employ Ordered Binary Decision Diagrams (OBDDs) as canonical representation for both Boolean circuit specifications and logic designs, but these methods require a large amount of memory and time. Due to these limitations, several models of Decision Diagrams have been studied and other verification techniques have been proposed. In this paper, we have used probabilistic verification with Galois (or finite) field GF(2m) modifying the CUDD package for the computation of signatures in classical OBDDs, and for the construction of Mod2-OBDDs (also known as ?-OBDDs). Mod2-OBDDs have been constructed with a two-level layer of ?-nodes using a positive Davio expansion (pDE) for a given variable. The sizes of the Mod2-OBDDs obtained with our method are lower than the Mod2-OBDDs sizes obtained with other similar methods.
