Construction of an Analysis Model of mRNA Markers in Menstrual Blood Based on Naïve Bayes and Multivariate Logistic Regression Methods.

To establish the menstrual blood identification model based on Naïve Bayes and multivariate logistic regression methods by using specific mRNA markers in menstrual blood detection technology combined with statistical methods, and to quantitatively distinguish menstrual blood from other body fluids.Body fluids including 86 menstrual blood, 48 peripheral blood, 48 vaginal secretions, 24 semen and 24 saliva samples were collected. RNA of the samples was extracted and cDNA was obtained by reverse transcription. Five menstrual blood-specific markers including members of the matrix metalloproteinase (MMP) family MMP3, MMP7, MMP11, progestogens associated endometrial protein (PAEP) and stanniocalcin-1 (STC1) were amplified and analyzed by electrophoresis. The results were analyzed by Naïve Bayes and multivariate logistic regression.The accuracy of the classification model constructed was 88.37% by Naïve Bayes and 91.86% by multivariate logistic regression. In non-menstrual blood samples, the distinguishing accuracy of peripheral blood, saliva and semen was generally higher than 90%, while the distinguishing accuracy of vaginal secretions was lower, which were 16.67% and 33.33%, respectively.The mRNA detection technology combined with statistical methods can be used to establish a classification and discrimination model for menstrual blood, which can distignuish the menstrual blood and other body fluids, and quantitative description of analysis results, which has a certain application value in body fluid stain identification.目的: 利用月经血特异性mRNA标志检测技术结合统计学方法，建立基于朴素贝叶斯和多元logistic回归方法的月经血鉴定模型，以定量区分月经血与其他体液。方法: 采集86份月经血、48份外周血、48份阴道分泌物、24份精液和24份唾液样本，经试剂盒提取样本RNA、反转录后得到cDNA，对5种月经血特异性标志，包括基质金属蛋白酶（matrix metalloproteinase，MMP）家族的成员MMP3、MMP7、MMP11，孕激素相关子宫内膜蛋白（progestogens associated endometrial protein，PAEP）和斯钙素-1（stanniocalcin-1，STC1）进行扩增和电泳检测分析。采用朴素贝叶斯和多元logistic回归对检测结果进行分析。结果: 朴素贝叶斯和多元logistic回归法构建的分类模型对月经血归类的准确率达88.37%和91.86%。在非月经血体液中，对外周血、唾液和精液的区分准确率普遍高于90%，分辨阴道分泌物时准确率较低，分别为16.67%和33.33%。结论: mRNA检测技术结合统计学方法可对月经血建立分类判别模型，可用于区分月经血和其他体液，并对分析结果进行定量描述，在斑迹鉴定中具有一定的应用价值。.