Research Progress of Metabolomics Techniques Combined with Machine Learning Algorithm in Wound Age Estimation / 法医学杂志

Wound age estimation is the core content in the practice of forensic medicine. Accurate estimation of wound age is a scientific question that needs to be urgently solved by forensic scientists at home and abroad. Metabolomics techniques can effectively detect endogenous metabolites produced by internal or external stimulating factors and describe the dynamic changes of metabolites in vivo. It has the advantages of strong operability, high detection efficiency and accurate quantitative results. Machine learning algorithm has special advantages in processing high-dimensional data sets, which can effectively mine biological information and truly reflect the physiological, disease or injury state of the body. It is a new technical means for efficiently processing high-throughput big data. This paper reviews the status and advantages of metabolomic techniques combined with machine learning algorithm in the research of wound age estimation, and provides new ideas for this research.

Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites / 法医学杂志

OBJECTIVES@#The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval (PMSI) estimation and the cause of death determination.@*METHODS@#The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group (n=50) and a postmortem (CO2 suffocation) immediately submersion group (n=50). Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest (RF) algorithm was used to screen several biomarkers to establish a model.@*RESULTS@#PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error (MAE) of the model was 0.847 h.@*CONCLUSIONS@#The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.

Relationship between Expression Changes of CB2R and Wound Age of Brain Contusion in Mice / 法医学杂志

Objective To investigate the expression of cannabinoid type 2 receptor （CB2R） at different time points after brain contusion and its relationship with wound age of mice. Methods A mouse brain contusion model was established with PCI3000 Precision Cortical Impactor. Expression changes of CB2R around the injured area were detected with immunohistochemical staining, immunofluorescent staining and Western blotting at different time points. Results Immunohistochemical staining results showed that only a few cells in the cerebral cortex of the sham operated group had CB2R positive expression. The ratio of CB2R positive cells gradually increased after injury and reached the peak twice at 12 h and 7 d post-injury, followed by a decrease to the normal level 28 d post-injury. The results of Western blotting were consistent with the immunohistochemical staining results. Immunofluorescent staining demonstrated that the changes of the ratio of CB2R positive cells in neurons, CB2R positive cells in monocytes and CB2R positive cells in astrocytes to the total cell number showed a single peak pattern, which peaked at 12 h, 1 d and 7 d post-injury, respectively. Conclusion The expression of CB2R after brain contusion in neurons, monocytes and astrocytes in mice suggests that it is likely to be involved in the regulation of the biological functions of those cells. The changes in CB2R are time-dependent, which suggests its potential applicability as a biological indicator for wound age estimation of brain contusion in forensic practice.