Identification Of Menstrual Blood At The Molecular Level

In the examination of forensic evidence,it is sometimes necessary to distinguish the bloodstains of the victimized woman to determine whether it is the traumatic bloodstain caused by the sexual assault or menstrual blood.In recent years,the use of RNA detection methods to infer the origin of body fluids has made great progress,but there are also many development space.This research aims to use molecular biological and genetic experimental technology to detect specific molecular markers in menstrual blood through five steps: sample collection,sample processing,RNA extraction,marker detection and result analysis to achieve accurate identification of menstrual blood.Six candidate primers of menstrual blood-specific markers were chosen through the literature,and their primers were designed.After verification by agarose electrophoresis and sequencing,it was confirmed that MMP3,PAEP-1,PAEP-2 and STC1 could amplify the expected target fragments.These 4 primers as well as MMP7,MMP11 and the housekeeping gene B2M were detected in 86 menstrual blood samples,48 ??peripheral blood samples,48??vaginal secretions samples,24 semen samples and 24 saliva samples.Single-label amplification was performed.The data was used to evaluate the sensitivity and specificity of the markers,and to construct menstrual blood identification models as a test set.The result showed that the RNA method has low detection limit and can successfully detect RNA diluted to 0.01 ng.The 6 primers of specific markers MMP3,MMP7,MMP11,PAEP-1,PAEP-2 and STC1 have high sensitivity in menstrual blood,and have high specificity in non-menstrual blood body fluids except vaginal secretions.The result also proved that the RNA method has the ability to distinguish mixed samples(such as a mixture of menstrual blood and semen or of peripheral blood and vaginal secretions).In this study,two classification algorithms,Naive Bayes and Multinomial Logistic Regression,were used to construct menstrual blood identification models.After performing Fisher test,it is determined that the NB classifier contained three feature points of MMP3,MMP7 and MMP11,and the MLR classifier contained 6 feature points of all specific markers.The results showed that the use of the classifier could not only get the body fluid category corresponding to the highest posterior probability,but also the value of the posterior probability,and can calculate the likelihood ratio so as to realize the statistical interpretation of the RNA test results.