Journal of Forensic Medicine最新文献

Objectives: To establish a simple and rapid qualitative and quantitative detection method of dexmedetomidine in blood.

Methods: Blood was separated on the Allure PFP Propyl liquid chromatography column with isocratic elution after it was precipitated by acetonitrile and filtered. Qualitative and quantitative analysis of dexmedetomidine was performed using positive ion scan mode and multi-reaction monitoring mode.

Results: The limit of detection of dexmedetomidine in blood was 0.2 ng/mL and the limit of quantification was 0.5 ng/mL. The linearity of the method was good in the range of 0.5-1 000 ng/mL, and the correlation coefficient was greater than 0.99. The accuracy of the method was 90.34%-112.67% and the extraction recovery was 50.05%-91.08%, with no significant matrix effect.

Conclusions: This method is simple, selective and suitable for the qualitative and quantitative analysis of dexmedetomidine in blood, which can provide a reference for drug-facilitated cases involving dexmedetomidine.

Skeleton and teeth are important biological samples. Due to their special structure and strong ability to resist degradation, they are ideal biological materials to retain DNA under natural condition. In many cases, such as historical figure identification, aged skeleton and teeth are usually the only biological samples. However, their DNA is in a state of trace, damage and degradation to different degrees, which requires special experimental treatment to achieve identification. This paper reviews the sample selection, DNA extraction, DNA enrichment and analysis approaches based on relevant research reports in recent years, aiming to promote the further development and improvement of the aged skeleton and teeth identification system.

Objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Objectives: The common differentially expressed mRNAs in brain, heart and liver tissues of deceased sudden infant death syndrome (SIDS) and infectious sudden death in infancy (ISDI) confirmed by autopsy was screened by bioinformatics to explore the common molecular markers and pathogenesis of SIDS and ISDI.

Methods: The datasets of GSE70422 and GSE136992 were downloaded, the limma of R software was used to screen differentially expressed mRNA in different tissue samples of SIDS and ISDI decedents for overlapping analysis. The clusterProfiler of R software was used to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The protein-protein interaction (PPI) network was constructed by STRING database, while the hub gene was screened by cytoHubba plug-in.

Results: Compared with the control group, there were 19 significant differentially expressed genes in the tissue samples of SIDS and ISDI decedents, among which 16 in the heart tissue and 3 in the liver tissue, and the astrotactin 1 (ASTN1) gene expression difference in the heart tissue was most significant. The PPI network identified Ras homolog family member A (RHOA), integrin subunit alpha 1 (ITGA1), and H2B clustered histone 5 (H2BC5) were hub genes. The analysis of GO and KEGG showed that differentially expressed genes were enriched in the molecular pathways of actin cytoskeleton regulation, focal adhesion and response to mycophenolic acid.

Conclusions: ASTN1, RHOA and ITGA1 may participate in the development of SIDS and ISDI. The enrichment of differentially expressed genes in immune and inflammatory pathways suggests a common molecular regulatory mechanism between SIDS and ISDI. These findings are expected to provide new biomarkers for molecular anatomy and forensic identification of SIDS and ISDI.