Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods / 法医学杂志

OBJECTIVES@#To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods.@*METHODS@#Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis.@*RESULTS@#The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples.@*CONCLUSIONS@#The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.

Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation / 法医学杂志

OBJECTIVES@#To investigate the effects of injury time, postmortem interval (PMI) and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B (Gpnmb), and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation.@*METHODS@#Test group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test.@*RESULTS@#The expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time (P<0.05), but had little correlation with PMI and postmortem storage temperature (P>0.05). The linear regression equation between injury time (y) and Gpnmb mRNA relative expression (x) was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate.@*CONCLUSIONS@#The expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.

Application Prospects and Prospect of Metabolomics in the Identification of Sudden Cardiac Death / 法医学杂志

In cases of sudden death, the prevention of sudden cardiac death and the analysis of the cause of death after sudden cardiac death have always been a difficult problem. Therefore, clinical research and forensic pathological identification of sudden cardiac death are of great significance. In recent years, metabolomics has gradually developed into a popular field of life science research. The detection of "metabolic fingerprints" of biological fluids can provide an important basis for early diagnosis of diseases and the discovery of potential biomarkers. This article reviews the current research status of sudden cardiac death and the research on metabolomics of cardiovascular diseases that is closely related to sudden cardiac death and analyzes the application prospects of metabolomics in the identification of the cause of sudden cardiac death.

Correlation between the Polymorphism of Coagulation-Related Genes and Lower Extremity Deep Venous Thrombosis / 法医学杂志

Objective To investigate the correlation between the polymorphism of 4 coagulation-related genes, rs1799963 （coagulation factor V gene Leiden）, rs6025 （prothrombin gene G20210A）, rs1042579 （thrombomodulin protein gene c.1418C>T） and rs1801131 （methylenetetrahydroflate reductase gene） and lower extremity deep venous thrombosis （LEDVT）. Methods The 4 genotypes mentioned above of 150 LEDVT patients and 153 healthy controls were detected by the kompetitive allele specific polymerase chain reaction （KASP）, then related blood biochemical indicators were collected, binary Logistic regression was established to screen the independent risk factors of LEDVT, and the correlation between polymorphism of 4 coagulation-related genes and LEDVT and its indicators under different genetic modes after adjusting confounding factors were analyzed. Results Five variables, D-dimer, fibrinogen degradation product, homocysteine, sex and age might be the risk factors of LEDVT. These variables were put into 4 genetic inheritance models, and adjusted in binary Logistic regression. The results suggested that the mutations of rs1042579 were correlated with LEDVT under dominant inheritance mode. Conclusion The gene polymorphism of rs1799963, rs6025 and rs1801131 has no significant correlation with the formation of LEDVT. The gene polymorphism of rs1042579 plays a role under dominant inheritance mode, and might be an independent risk factor for formation of LEDVT.

Estimating Postmortem Interval by Protein Chip Detection Technology Combined with Multidimensional Statistics / 法医学杂志

Objective To obtain the protein expression profile of rat liver tissue after death by the 2100 bioanalyzer combined with protein chip, and infer the relationship between protein expression profile and postmortem interval. Methods Rats were killed by abdominal anesthesia and placed at 16 ℃. Water-soluble proteins in liver tissues were extracted at 14 time points after death. The expression profile data of proteins with relative molecular weight of 14 000-230 000 were obtained using protein chip, and principal component analysis （PCA）, partial least squares-discriminant analysis （PLS-DA） and Fisher discriminant were used to analyze the data. Results According to the changes of protein expression profile, the postmortem interval was divided into group A （0 d）, group B （1-9 d）, group C （12-30 d） according to the result of PLS-DA. The prediction accuracy of the training set and test set of the model were all 100.0%, and the internal cross-validation of the training set was 100.0% according to Fisher discriminant. The Fisher discriminant model at each time point of group B and C was established to narrow the time window of postmortem interval estimation. The prediction accuracy of the training set and test set were all 100.0%, and the internal cross-validation accuracy of the training set was 100.0% in group B. The prediction accuracy of the training set and test set were respectively 95.2% and 78.6% in group C, and the internal cross-validation of the training set was 88.1%. Conclusion Protein chip detection technology can quickly and easily obtain the expression profile of water-soluble proteins of rat liver tissue with a relative molecular weight of 14 000-230 000 at different time points after death. PLS-DA and Fisher discriminant models are established to classify and predict the postmortem interval, in order to provide new ideas and methods for postmortem interval estimation.

Study on Urinary Metabolic Profile in Rats with Deep Venous Thrombosis Based on Pattern Recognition / 法医学杂志

OBJECTIVES@#To study the urinary metabolic profile in rats with deep venous thrombosis （DVT） based on metabolomics and to screen out small molecular biomarkers for the diagnosis and forensic identification of DVT.@*METHODS@#Inferior vena cava of rats was ligated to construct DVT models. The rats were randomly divided into three groups： DVT, sham, and control groups, 10 in each group. The urine of DVT and sham rats was collected during 24 hours in the metabolic cage at 48 hours after operating, meanwhile, 24 hours urine was collected in control group. The metabolic profile was analyzed by nuclear magnetic resonance. SIMCA-P 14.1 software was used for pattern recognition. The variable importance in projection （VIP） value from orthogonal PLS-DA （OPLS-DA） model combined with Mann-Whitney U test were used to search the different metabolites in the urine.@*RESULTS@#The metabolic profiles of urine from DVT, sham, and control groups had significant differences. The DVT, sham, and control groups could be distinguished by the partial least squares method-discriminant analysis （PLS-DA） model. Compared with the urine of the rats in control groups, the levels of leucine, glutamine, creatine, creatinine and sucrose in the urine of DVT rats were up-regulated, and the levels of 3-hydroxybutyrate, lactate, acetone, α-oxoglutarate, citrate and hippurate were down-regulated.@*CONCLUSIONS@#The different metabolites in the urine of DVT rats are expected to become its candidate biomarkers. The results can provide a research basis for the diagnosis, treatment and forensic identification of DVT.

Basophil CD63 expression in the blood of the anaphylactic shock rat / 法医学杂志

OBJECTIVE@#To explore the value of flow cytometry in anaphylactic shock diagnosis by CD63 expression being detected using flow cytometry to conform the activation of basophils.@*METHODS@#Sixteen rats were randomly divided into two groups: control group and anaphylactic shock group. The model of anaphylactic shock rat with ovalbumin injection was established. CD63, CD45 and CD203c antibody combination, flow cytometry was employed to detected blood basophil CD63 expression. Immunofluorescence method was employed to observe the CD63 immunofluorescence staining in the rat lung tissue.@*RESULTS@#(1) Pure basophils were obtained by CD45 and CD203c gating. (2) The percentages of basophils CD63 were (17.34 +/- 2.04)% and (1.52 +/- 0.35)% in the experimental and control group, respectively. The differences between two groups were statistically significant (P < 0.01). (3) Compared with the control group, the expression of CD63 in basophils increased in anaphylactic shock lung tissue.@*CONCLUSION@#The detection of CD63 by flow cytometry could be the supplement of vivo allergic reactions and have good clinical value.