Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those ...Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those methods are largely restricted due to nonnegligible residual frequency.This paper proposes a new dual-channel method for fast acquisition of long PN-code.In the proposed method,both non-overlapping local PNcode blocks are employed to correlate with input sample block;the detection process is eased through finding the maximum value among correlation results and verification is made with all the full and partial peaks taken into account.False alarm probabilities from analysis of the verification process are derived.Both theoretical and Monte Carlo simulations reveal that,with respect to acquisition probability and mean acquisition time under the same false alarm rate,dual-channel method has advantage over zero-padding and XFAST based folding methods under certain false alarm probabilities.展开更多
目的探索胃癌组蛋白H3第4位赖氨酸的三甲基化(trimethylation of lysine4 on histone H3,H3K4me3)修饰相关长链非编码RNA(long non-coding RNA,LncRNA)特征,构建相关预后模型并预测胃癌免疫治疗疗效。方法从癌症基因组图谱数据库下载胃...目的探索胃癌组蛋白H3第4位赖氨酸的三甲基化(trimethylation of lysine4 on histone H3,H3K4me3)修饰相关长链非编码RNA(long non-coding RNA,LncRNA)特征,构建相关预后模型并预测胃癌免疫治疗疗效。方法从癌症基因组图谱数据库下载胃癌相关转录组测序数据和对应的患者临床资料,通过构建H3K4me3相关调节因子基因与LncRNA的共表达网络识别H3K4me3修饰相关LncRNA,并将癌症基因组图谱数据库中370例符合筛选标准的胃癌患者样本(整体组)按1:1随机抽样划分为训练组(n=185)和验证组(n=185)。随后基于单因素Cox回归、Lasoo回归分析构建H3K4me3相关LncRNA预后风险评分模型并进行内部验证。Kaplan-Meier生存分析和受试者操作特征曲线(receiver operating characteristic curve,ROC曲线)被用于验证模型的预测性能。通过单因素和多因素Cox回归分析评估风险评分等临床指标的预后预测价值。结合风险评分、年龄和肿瘤TNM分期构建预测胃癌患者总生存率的列线图模型,ROC曲线与校准图被用于评估列线图的预测准确性。借助共识聚类识别异质性聚类亚群并进行免疫治疗疗效预测。结果基于共表达网络关系识别了14个具有预后价值的H3K4me3相关LncRNA并构建了相关风险模型及评价体系。根据训练组预后风险评分模型获得的中位风险评分将训练组、验证组和整体组胃癌患者划分为高、低风险,Kaplan-Meier生存曲线显示低风险患者的总体生存情况要优于高风险患者(P<0.05)。此外,该模型在训练组中预测胃癌患者1、3、5年总生存率的曲线下面积(area undercurve,AUC)分别为0.708、0.730、0.770,在验证组中分别为0.690、0.648、0.713,而在整体组中分别为0.697、0.670、0.724。多因素Cox回归分析显示基于H3K4me3相关LncRNA构建的风险评分模型是预测胃癌患者预后的独立因素(P<0.001)。构建的列线图预测胃癌患者1、2、3年总生存率的AUC分别为0.727、0.780、0.717,且其校准曲线与理想曲线相接近。基于共识聚类算法进一步识别了2种具有异质性免疫特征的H3K4me3-LncRNA亚群,其中亚组Ⅱ具有更高的免疫细胞浸润水平和更强的免疫应答潜力,并对5-氟尿嘧啶、奥沙利铂等显示出更高的药物敏感性,而亚组I则可能对磷脂酰肌醇3-激酶特异性抑制剂具有更高的敏感性。结论本研究构建了一个H3K4me3-LncRNA风险评分模型以预测胃癌患者的预后,并揭示了其异质性微观特征及在预测免疫治疗疗效方面的潜在价值。展开更多
文摘Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those methods are largely restricted due to nonnegligible residual frequency.This paper proposes a new dual-channel method for fast acquisition of long PN-code.In the proposed method,both non-overlapping local PNcode blocks are employed to correlate with input sample block;the detection process is eased through finding the maximum value among correlation results and verification is made with all the full and partial peaks taken into account.False alarm probabilities from analysis of the verification process are derived.Both theoretical and Monte Carlo simulations reveal that,with respect to acquisition probability and mean acquisition time under the same false alarm rate,dual-channel method has advantage over zero-padding and XFAST based folding methods under certain false alarm probabilities.
